Overview

Brought to you by YData

Dataset statistics

Number of variables112
Number of observations4515661
Missing cells350029119
Missing cells (%)69.2%
Total size in memory3.8 GiB
Average record size in memory896.0 B

Variable types

Text112

Dataset

DescriptionUS NMNH Extant Specimen Records 0052487-241126133413365
URLhttps://doi.org/10.15468/dl.wttrju

Alerts

institutionID has constant value "urn:lsid:biocol.org:col:15463" Constant
collectionID has constant value "urn:uuid:60e28f81-e634-4869-aa3e-732caed713c8" Constant
institutionCode has constant value "US" Constant
collectionCode has constant value "US" Constant
datasetName has constant value "NMNH Extant Biology" Constant
eventType has constant value "-7.38" Constant
samplingProtocol has constant value "400.0" Constant
countryCode has constant value "1872" Constant
verbatimSRS has constant value "San Francisco" Constant
lithostratigraphicTerms has constant value "500.0" Constant
bed has constant value "Riccardia pinguis" Constant
identificationID has constant value "Variety" Constant
taxonID has constant value "Metzgeriales" Constant
acceptedNameUsageID has constant value "Aneuraceae" Constant
namePublishedInID has constant value "Riccardia" Constant
nameAccordingTo has constant value "variety" Constant
nomenclaturalCode has constant value "Skog, Laurence E." Constant
taxonRemarks has constant value "Plantae" Constant
catalogNumber has 604654 (13.4%) missing values Missing
recordedBy has 54378 (1.2%) missing values Missing
lifeStage has 4152582 (92.0%) missing values Missing
preparations has 4381212 (97.0%) missing values Missing
associatedMedia has 318147 (7.0%) missing values Missing
associatedSequences has 4515310 (> 99.9%) missing values Missing
occurrenceRemarks has 4424129 (98.0%) missing values Missing
organismName has 4515658 (> 99.9%) missing values Missing
eventType has 4515660 (> 99.9%) missing values Missing
fieldNumber has 4515399 (> 99.9%) missing values Missing
eventDate has 499507 (11.1%) missing values Missing
startDayOfYear has 707937 (15.7%) missing values Missing
endDayOfYear has 706297 (15.6%) missing values Missing
year has 499507 (11.1%) missing values Missing
month has 700051 (15.5%) missing values Missing
day has 1180026 (26.1%) missing values Missing
verbatimEventDate has 2995056 (66.3%) missing values Missing
habitat has 4009333 (88.8%) missing values Missing
samplingProtocol has 4515660 (> 99.9%) missing values Missing
sampleSizeValue has 4515659 (> 99.9%) missing values Missing
locationID has 4473993 (99.1%) missing values Missing
continent has 66158 (1.5%) missing values Missing
waterBody has 4496088 (99.6%) missing values Missing
islandGroup has 4403077 (97.5%) missing values Missing
island has 4139168 (91.7%) missing values Missing
countryCode has 4515660 (> 99.9%) missing values Missing
stateProvince has 1002183 (22.2%) missing values Missing
county has 3778676 (83.7%) missing values Missing
locality has 332028 (7.4%) missing values Missing
verbatimLocality has 4515656 (> 99.9%) missing values Missing
minimumElevationInMeters has 2860984 (63.4%) missing values Missing
maximumElevationInMeters has 4017410 (89.0%) missing values Missing
minimumDepthInMeters has 4475632 (99.1%) missing values Missing
maximumDepthInMeters has 4478965 (99.2%) missing values Missing
verbatimDepth has 4494022 (99.5%) missing values Missing
decimalLatitude has 3845453 (85.2%) missing values Missing
decimalLongitude has 3845454 (85.2%) missing values Missing
geodeticDatum has 4485859 (99.3%) missing values Missing
coordinateUncertaintyInMeters has 4509192 (99.9%) missing values Missing
coordinatePrecision has 4515658 (> 99.9%) missing values Missing
pointRadiusSpatialFit has 4515656 (> 99.9%) missing values Missing
verbatimCoordinates has 4515657 (> 99.9%) missing values Missing
verbatimLatitude has 4477670 (99.2%) missing values Missing
verbatimLongitude has 4477686 (99.2%) missing values Missing
verbatimCoordinateSystem has 4478628 (99.2%) missing values Missing
verbatimSRS has 4515660 (> 99.9%) missing values Missing
footprintSpatialFit has 4515658 (> 99.9%) missing values Missing
georeferenceProtocol has 4388537 (97.2%) missing values Missing
georeferenceRemarks has 4515150 (> 99.9%) missing values Missing
geologicalContextID has 4515657 (> 99.9%) missing values Missing
earliestEonOrLowestEonothem has 4515654 (> 99.9%) missing values Missing
latestEonOrHighestEonothem has 4515654 (> 99.9%) missing values Missing
latestEraOrHighestErathem has 4515658 (> 99.9%) missing values Missing
earliestPeriodOrLowestSystem has 4515654 (> 99.9%) missing values Missing
earliestEpochOrLowestSeries has 4515654 (> 99.9%) missing values Missing
latestEpochOrHighestSeries has 4515659 (> 99.9%) missing values Missing
latestAgeOrHighestStage has 4515657 (> 99.9%) missing values Missing
lowestBiostratigraphicZone has 4515658 (> 99.9%) missing values Missing
highestBiostratigraphicZone has 4515658 (> 99.9%) missing values Missing
lithostratigraphicTerms has 4515660 (> 99.9%) missing values Missing
formation has 4515658 (> 99.9%) missing values Missing
member has 4515654 (> 99.9%) missing values Missing
bed has 4515660 (> 99.9%) missing values Missing
identificationID has 4515660 (> 99.9%) missing values Missing
identificationQualifier has 4504655 (99.8%) missing values Missing
typeStatus has 4399315 (97.4%) missing values Missing
identifiedBy has 3958097 (87.7%) missing values Missing
identifiedByID has 4515655 (> 99.9%) missing values Missing
dateIdentified has 4515654 (> 99.9%) missing values Missing
identificationReferences has 4515655 (> 99.9%) missing values Missing
identificationVerificationStatus has 4515654 (> 99.9%) missing values Missing
identificationRemarks has 4515654 (> 99.9%) missing values Missing
taxonID has 4515660 (> 99.9%) missing values Missing
scientificNameID has 4515655 (> 99.9%) missing values Missing
acceptedNameUsageID has 4515660 (> 99.9%) missing values Missing
nameAccordingToID has 4515655 (> 99.9%) missing values Missing
namePublishedInID has 4515660 (> 99.9%) missing values Missing
acceptedNameUsage has 4515655 (> 99.9%) missing values Missing
parentNameUsage has 4515659 (> 99.9%) missing values Missing
nameAccordingTo has 4515660 (> 99.9%) missing values Missing
namePublishedInYear has 4515656 (> 99.9%) missing values Missing
phylum has 3795307 (84.0%) missing values Missing
class has 166450 (3.7%) missing values Missing
order has 53019 (1.2%) missing values Missing
family has 49040 (1.1%) missing values Missing
subgenus has 4515572 (> 99.9%) missing values Missing
infraspecificEpithet has 4196068 (92.9%) missing values Missing
cultivarEpithet has 4515659 (> 99.9%) missing values Missing
taxonRank has 4196350 (92.9%) missing values Missing
scientificNameAuthorship has 491289 (10.9%) missing values Missing
vernacularName has 4515658 (> 99.9%) missing values Missing
nomenclaturalCode has 4515660 (> 99.9%) missing values Missing
nomenclaturalStatus has 4515659 (> 99.9%) missing values Missing
taxonRemarks has 4515659 (> 99.9%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique

Reproduction

Analysis started2025-01-14 16:41:47.797700
Analysis finished2025-01-14 16:45:01.983197
Duration3 minutes and 14.19 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct4515661
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size34.5 MiB
2025-01-14T11:45:04.527485image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters45156610
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4515661 ?
Unique (%)100.0%

Sample

1st row1320179379
2nd row1675994101
3rd row2592240144
4th row2571494932
5th row3357270605
ValueCountFrequency (%)
1320179379 1
 
< 0.1%
1320180447 1
 
< 0.1%
3897771070 1
 
< 0.1%
1320181031 1
 
< 0.1%
1321730416 1
 
< 0.1%
1321730340 1
 
< 0.1%
3467345455 1
 
< 0.1%
1456364699 1
 
< 0.1%
1321730091 1
 
< 0.1%
1320184062 1
 
< 0.1%
Other values (4515651) 4515651
> 99.9%
2025-01-14T11:45:06.747322image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6587745
14.6%
2 6301614
14.0%
3 5901629
13.1%
5 4291608
9.5%
6 3896698
8.6%
4 3891530
8.6%
7 3755094
8.3%
8 3664337
8.1%
0 3571035
7.9%
9 3295320
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 45156610
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6587745
14.6%
2 6301614
14.0%
3 5901629
13.1%
5 4291608
9.5%
6 3896698
8.6%
4 3891530
8.6%
7 3755094
8.3%
8 3664337
8.1%
0 3571035
7.9%
9 3295320
7.3%

Most occurring scripts

ValueCountFrequency (%)
Common 45156610
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6587745
14.6%
2 6301614
14.0%
3 5901629
13.1%
5 4291608
9.5%
6 3896698
8.6%
4 3891530
8.6%
7 3755094
8.3%
8 3664337
8.1%
0 3571035
7.9%
9 3295320
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45156610
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6587745
14.6%
2 6301614
14.0%
3 5901629
13.1%
5 4291608
9.5%
6 3896698
8.6%
4 3891530
8.6%
7 3755094
8.3%
8 3664337
8.1%
0 3571035
7.9%
9 3295320
7.3%

modified
Text

Distinct180669
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size34.5 MiB
2025-01-14T11:45:06.964288image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters85797559
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59498 ?
Unique (%)1.3%

Sample

1st row2016-08-30 13:42:00
2nd row2022-10-26 17:57:00
3rd row2020-05-10 23:06:00
4th row2020-04-09 11:53:00
5th row2021-09-10 21:16:00
ValueCountFrequency (%)
2017-08-04 233209
 
2.6%
2022-10-26 209132
 
2.3%
2022-06-03 121741
 
1.3%
2022-09-08 97141
 
1.1%
2017-12-19 94237
 
1.0%
2022-06-02 84448
 
0.9%
2024-10-17 76731
 
0.8%
2016-08-29 71251
 
0.8%
2016-08-30 70049
 
0.8%
2019-07-12 61211
 
0.7%
Other values (3909) 7912172
87.6%
2025-01-14T11:45:07.233781image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23062874
26.9%
2 11939180
13.9%
1 11301135
13.2%
- 9031322
 
10.5%
: 9031322
 
10.5%
4515661
 
5.3%
3 2960518
 
3.5%
8 2607270
 
3.0%
9 2572066
 
3.0%
4 2388421
 
2.8%
Other values (3) 6387790
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63219254
73.7%
Dash Punctuation 9031322
 
10.5%
Other Punctuation 9031322
 
10.5%
Space Separator 4515661
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23062874
36.5%
2 11939180
18.9%
1 11301135
17.9%
3 2960518
 
4.7%
8 2607270
 
4.1%
9 2572066
 
4.1%
4 2388421
 
3.8%
7 2315554
 
3.7%
5 2112325
 
3.3%
6 1959911
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 9031322
100.0%
Other Punctuation
ValueCountFrequency (%)
: 9031322
100.0%
Space Separator
ValueCountFrequency (%)
4515661
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85797559
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23062874
26.9%
2 11939180
13.9%
1 11301135
13.2%
- 9031322
 
10.5%
: 9031322
 
10.5%
4515661
 
5.3%
3 2960518
 
3.5%
8 2607270
 
3.0%
9 2572066
 
3.0%
4 2388421
 
2.8%
Other values (3) 6387790
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85797559
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23062874
26.9%
2 11939180
13.9%
1 11301135
13.2%
- 9031322
 
10.5%
: 9031322
 
10.5%
4515661
 
5.3%
3 2960518
 
3.5%
8 2607270
 
3.0%
9 2572066
 
3.0%
4 2388421
 
2.8%
Other values (3) 6387790
 
7.4%

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.5 MiB
2025-01-14T11:45:07.301446image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters130954169
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:lsid:biocol.org:col:15463
2nd rowurn:lsid:biocol.org:col:15463
3rd rowurn:lsid:biocol.org:col:15463
4th rowurn:lsid:biocol.org:col:15463
5th rowurn:lsid:biocol.org:col:15463
ValueCountFrequency (%)
urn:lsid:biocol.org:col:15463 4515661
100.0%
2025-01-14T11:45:07.408637image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 18062644
13.8%
: 18062644
13.8%
l 13546983
 
10.3%
i 9031322
 
6.9%
r 9031322
 
6.9%
c 9031322
 
6.9%
g 4515661
 
3.4%
6 4515661
 
3.4%
4 4515661
 
3.4%
5 4515661
 
3.4%
Other values (8) 36125288
27.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 85797559
65.5%
Other Punctuation 22578305
 
17.2%
Decimal Number 22578305
 
17.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 18062644
21.1%
l 13546983
15.8%
i 9031322
10.5%
r 9031322
10.5%
c 9031322
10.5%
g 4515661
 
5.3%
u 4515661
 
5.3%
b 4515661
 
5.3%
d 4515661
 
5.3%
s 4515661
 
5.3%
Decimal Number
ValueCountFrequency (%)
6 4515661
20.0%
4 4515661
20.0%
5 4515661
20.0%
1 4515661
20.0%
3 4515661
20.0%
Other Punctuation
ValueCountFrequency (%)
: 18062644
80.0%
. 4515661
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 85797559
65.5%
Common 45156610
34.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 18062644
21.1%
l 13546983
15.8%
i 9031322
10.5%
r 9031322
10.5%
c 9031322
10.5%
g 4515661
 
5.3%
u 4515661
 
5.3%
b 4515661
 
5.3%
d 4515661
 
5.3%
s 4515661
 
5.3%
Common
ValueCountFrequency (%)
: 18062644
40.0%
6 4515661
 
10.0%
4 4515661
 
10.0%
5 4515661
 
10.0%
1 4515661
 
10.0%
. 4515661
 
10.0%
3 4515661
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130954169
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 18062644
13.8%
: 18062644
13.8%
l 13546983
 
10.3%
i 9031322
 
6.9%
r 9031322
 
6.9%
c 9031322
 
6.9%
g 4515661
 
3.4%
6 4515661
 
3.4%
4 4515661
 
3.4%
5 4515661
 
3.4%
Other values (8) 36125288
27.6%

collectionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.5 MiB
2025-01-14T11:45:07.467576image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters203204745
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:60e28f81-e634-4869-aa3e-732caed713c8
2nd rowurn:uuid:60e28f81-e634-4869-aa3e-732caed713c8
3rd rowurn:uuid:60e28f81-e634-4869-aa3e-732caed713c8
4th rowurn:uuid:60e28f81-e634-4869-aa3e-732caed713c8
5th rowurn:uuid:60e28f81-e634-4869-aa3e-732caed713c8
ValueCountFrequency (%)
urn:uuid:60e28f81-e634-4869-aa3e-732caed713c8 4515661
100.0%
2025-01-14T11:45:07.575801image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 18062644
 
8.9%
3 18062644
 
8.9%
- 18062644
 
8.9%
e 18062644
 
8.9%
6 13546983
 
6.7%
a 13546983
 
6.7%
u 13546983
 
6.7%
d 9031322
 
4.4%
2 9031322
 
4.4%
1 9031322
 
4.4%
Other values (10) 63219254
31.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94828881
46.7%
Lowercase Letter 81281898
40.0%
Dash Punctuation 18062644
 
8.9%
Other Punctuation 9031322
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 18062644
19.0%
3 18062644
19.0%
6 13546983
14.3%
2 9031322
9.5%
1 9031322
9.5%
4 9031322
9.5%
7 9031322
9.5%
0 4515661
 
4.8%
9 4515661
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
e 18062644
22.2%
a 13546983
16.7%
u 13546983
16.7%
d 9031322
11.1%
c 9031322
11.1%
r 4515661
 
5.6%
f 4515661
 
5.6%
i 4515661
 
5.6%
n 4515661
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 18062644
100.0%
Other Punctuation
ValueCountFrequency (%)
: 9031322
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 121922847
60.0%
Latin 81281898
40.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 18062644
14.8%
3 18062644
14.8%
- 18062644
14.8%
6 13546983
11.1%
2 9031322
7.4%
1 9031322
7.4%
: 9031322
7.4%
4 9031322
7.4%
7 9031322
7.4%
0 4515661
 
3.7%
Latin
ValueCountFrequency (%)
e 18062644
22.2%
a 13546983
16.7%
u 13546983
16.7%
d 9031322
11.1%
c 9031322
11.1%
r 4515661
 
5.6%
f 4515661
 
5.6%
i 4515661
 
5.6%
n 4515661
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 203204745
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 18062644
 
8.9%
3 18062644
 
8.9%
- 18062644
 
8.9%
e 18062644
 
8.9%
6 13546983
 
6.7%
a 13546983
 
6.7%
u 13546983
 
6.7%
d 9031322
 
4.4%
2 9031322
 
4.4%
1 9031322
 
4.4%
Other values (10) 63219254
31.1%

institutionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.5 MiB
2025-01-14T11:45:07.618343image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters9031322
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS
ValueCountFrequency (%)
us 4515661
100.0%
2025-01-14T11:45:07.712022image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 4515661
50.0%
S 4515661
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 9031322
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 4515661
50.0%
S 4515661
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9031322
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 4515661
50.0%
S 4515661
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9031322
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 4515661
50.0%
S 4515661
50.0%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.5 MiB
2025-01-14T11:45:07.752882image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters9031322
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS
ValueCountFrequency (%)
us 4515661
100.0%
2025-01-14T11:45:07.847562image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 4515661
50.0%
S 4515661
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 9031322
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 4515661
50.0%
S 4515661
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9031322
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 4515661
50.0%
S 4515661
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9031322
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 4515661
50.0%
S 4515661
50.0%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.5 MiB
2025-01-14T11:45:07.893582image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters85797559
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Extant Biology
2nd rowNMNH Extant Biology
3rd rowNMNH Extant Biology
4th rowNMNH Extant Biology
5th rowNMNH Extant Biology
ValueCountFrequency (%)
nmnh 4515661
33.3%
extant 4515661
33.3%
biology 4515661
33.3%
2025-01-14T11:45:07.992089image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 9031322
 
10.5%
9031322
 
10.5%
t 9031322
 
10.5%
o 9031322
 
10.5%
M 4515661
 
5.3%
H 4515661
 
5.3%
E 4515661
 
5.3%
x 4515661
 
5.3%
a 4515661
 
5.3%
n 4515661
 
5.3%
Other values (5) 22578305
26.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 49672271
57.9%
Uppercase Letter 27093966
31.6%
Space Separator 9031322
 
10.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 9031322
18.2%
o 9031322
18.2%
x 4515661
9.1%
a 4515661
9.1%
n 4515661
9.1%
i 4515661
9.1%
l 4515661
9.1%
g 4515661
9.1%
y 4515661
9.1%
Uppercase Letter
ValueCountFrequency (%)
N 9031322
33.3%
M 4515661
16.7%
H 4515661
16.7%
E 4515661
16.7%
B 4515661
16.7%
Space Separator
ValueCountFrequency (%)
9031322
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 76766237
89.5%
Common 9031322
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 9031322
11.8%
t 9031322
11.8%
o 9031322
11.8%
M 4515661
 
5.9%
H 4515661
 
5.9%
E 4515661
 
5.9%
x 4515661
 
5.9%
a 4515661
 
5.9%
n 4515661
 
5.9%
B 4515661
 
5.9%
Other values (4) 18062644
23.5%
Common
ValueCountFrequency (%)
9031322
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85797559
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 9031322
 
10.5%
9031322
 
10.5%
t 9031322
 
10.5%
o 9031322
 
10.5%
M 4515661
 
5.3%
H 4515661
 
5.3%
E 4515661
 
5.3%
x 4515661
 
5.3%
a 4515661
 
5.3%
n 4515661
 
5.3%
Other values (5) 22578305
26.3%

basisOfRecord
Text

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size34.5 MiB
2025-01-14T11:45:08.046417image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length17
Mean length17.01103094
Min length16

Characters and Unicode

Total characters76816049
Distinct characters21
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPreservedSpecimen
2nd rowPreservedSpecimen
3rd rowPreservedSpecimen
4th rowPreservedSpecimen
5th rowPreservedSpecimen
ValueCountFrequency (%)
preservedspecimen 4465843
98.9%
machineobservation 49815
 
1.1%
humanobservation 3
 
< 0.1%
2025-01-14T11:45:08.163553image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 22428848
29.2%
r 8981504
11.7%
n 4565479
 
5.9%
i 4565476
 
5.9%
s 4515661
 
5.9%
v 4515661
 
5.9%
c 4515658
 
5.9%
m 4465846
 
5.8%
P 4465843
 
5.8%
p 4465843
 
5.8%
Other values (11) 9330230
12.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 67784727
88.2%
Uppercase Letter 9031322
 
11.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 22428848
33.1%
r 8981504
13.3%
n 4565479
 
6.7%
i 4565476
 
6.7%
s 4515661
 
6.7%
v 4515661
 
6.7%
c 4515658
 
6.7%
m 4465846
 
6.6%
p 4465843
 
6.6%
d 4465843
 
6.6%
Other values (6) 298908
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
P 4465843
49.4%
S 4465843
49.4%
O 49818
 
0.6%
M 49815
 
0.6%
H 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 76816049
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 22428848
29.2%
r 8981504
11.7%
n 4565479
 
5.9%
i 4565476
 
5.9%
s 4515661
 
5.9%
v 4515661
 
5.9%
c 4515658
 
5.9%
m 4465846
 
5.8%
P 4465843
 
5.8%
p 4465843
 
5.8%
Other values (11) 9330230
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76816049
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 22428848
29.2%
r 8981504
11.7%
n 4565479
 
5.9%
i 4565476
 
5.9%
s 4515661
 
5.9%
v 4515661
 
5.9%
c 4515658
 
5.9%
m 4465846
 
5.8%
P 4465843
 
5.8%
p 4465843
 
5.8%
Other values (11) 9330230
12.1%

occurrenceID
Text

Unique 

Distinct4515661
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size34.5 MiB
2025-01-14T11:45:10.304534image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters284486643
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4515661 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/383aab1ce-8b35-4007-8eba-472b592b7a99
2nd rowhttp://n2t.net/ark:/65665/3c8351e79-8b3b-4df0-80be-cb019ba60185
3rd rowhttp://n2t.net/ark:/65665/3c8377593-a51b-4b6a-835d-649053b2ef0f
4th rowhttp://n2t.net/ark:/65665/383b388e9-b7cc-4b41-95cc-e0a1b092179a
5th rowhttp://n2t.net/ark:/65665/3c83e5abc-b64e-45a4-aa42-faf5abc93792
ValueCountFrequency (%)
http://n2t.net/ark:/65665/383aab1ce-8b35-4007-8eba-472b592b7a99 1
 
< 0.1%
http://n2t.net/ark:/65665/383b6d73e-eb70-4b52-81b8-336878ca92f0 1
 
< 0.1%
http://n2t.net/ark:/65665/3c84a8b17-83ab-45b2-bb8e-ccea78a7e003 1
 
< 0.1%
http://n2t.net/ark:/65665/383be1f82-08fe-4004-9374-3793b1df97c5 1
 
< 0.1%
http://n2t.net/ark:/65665/3c842b3ee-b36e-41da-867e-a7c09def7524 1
 
< 0.1%
http://n2t.net/ark:/65665/3c841ed6b-df48-4633-aae7-d3e846a86aa3 1
 
< 0.1%
http://n2t.net/ark:/65665/383b77fe7-0ea2-407e-bde8-bba5ef603c4a 1
 
< 0.1%
http://n2t.net/ark:/65665/3c8411b46-27ee-4d70-ab07-e1bd72f2e83a 1
 
< 0.1%
http://n2t.net/ark:/65665/3c83f60ef-2f0d-451e-986a-e0c2dfb03675 1
 
< 0.1%
http://n2t.net/ark:/65665/383e13640-df35-46e1-befc-1068e49e2444 1
 
< 0.1%
Other values (4515651) 4515651
> 99.9%
2025-01-14T11:45:12.444144image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 22578305
 
7.9%
6 22016321
 
7.7%
- 18062644
 
6.3%
t 18062644
 
6.3%
5 17496925
 
6.2%
a 14109308
 
5.0%
e 12988442
 
4.6%
4 12983714
 
4.6%
2 12981604
 
4.6%
3 12976062
 
4.6%
Other values (16) 120230674
42.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 123048299
43.3%
Lowercase Letter 107250412
37.7%
Other Punctuation 36125288
 
12.7%
Dash Punctuation 18062644
 
6.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 18062644
16.8%
a 14109308
13.2%
e 12988442
12.1%
b 9594278
8.9%
n 9031322
8.4%
d 8469759
7.9%
c 8468487
7.9%
f 8463528
7.9%
k 4515661
 
4.2%
r 4515661
 
4.2%
Other values (2) 9031322
8.4%
Decimal Number
ValueCountFrequency (%)
6 22016321
17.9%
5 17496925
14.2%
4 12983714
10.6%
2 12981604
10.6%
3 12976062
10.5%
9 9599378
7.8%
8 9594754
7.8%
1 8470306
 
6.9%
0 8465201
 
6.9%
7 8464034
 
6.9%
Other Punctuation
ValueCountFrequency (%)
/ 22578305
62.5%
: 9031322
 
25.0%
. 4515661
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 18062644
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 177236231
62.3%
Latin 107250412
37.7%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 22578305
12.7%
6 22016321
12.4%
- 18062644
10.2%
5 17496925
9.9%
4 12983714
7.3%
2 12981604
7.3%
3 12976062
7.3%
9 9599378
 
5.4%
8 9594754
 
5.4%
: 9031322
 
5.1%
Other values (4) 29915202
16.9%
Latin
ValueCountFrequency (%)
t 18062644
16.8%
a 14109308
13.2%
e 12988442
12.1%
b 9594278
8.9%
n 9031322
8.4%
d 8469759
7.9%
c 8468487
7.9%
f 8463528
7.9%
k 4515661
 
4.2%
r 4515661
 
4.2%
Other values (2) 9031322
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 284486643
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 22578305
 
7.9%
6 22016321
 
7.7%
- 18062644
 
6.3%
t 18062644
 
6.3%
5 17496925
 
6.2%
a 14109308
 
5.0%
e 12988442
 
4.6%
4 12983714
 
4.6%
2 12981604
 
4.6%
3 12976062
 
4.6%
Other values (16) 120230674
42.3%

catalogNumber
Text

Missing 

Distinct3682462
Distinct (%)94.2%
Missing604654
Missing (%)13.4%
Memory size34.5 MiB
2025-01-14T11:45:14.399303image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length10
Mean length9.635907069
Min length4

Characters and Unicode

Total characters37686100
Distinct characters48
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3481841 ?
Unique (%)89.0%

Sample

1st rowUS 213621
2nd rowUS 2144946
3rd rowUS 3113222
4th rowUS 2583825
5th rowUS 3026466
ValueCountFrequency (%)
us 3868231
49.7%
sem 238
 
< 0.1%
146
 
< 0.1%
stub 135
 
< 0.1%
1 133
 
< 0.1%
micrograph 103
 
< 0.1%
169920 59
 
< 0.1%
2 44
 
< 0.1%
3 40
 
< 0.1%
95340 36
 
< 0.1%
Other values (3682069) 3910894
50.3%
2025-01-14T11:45:16.388231image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 3911382
10.4%
U 3911009
10.4%
3869052
10.3%
2 3434134
9.1%
1 3365755
8.9%
3 3065165
8.1%
5 2346706
 
6.2%
6 2337766
 
6.2%
4 2336936
 
6.2%
7 2291395
 
6.1%
Other values (38) 6816800
18.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25862216
68.6%
Uppercase Letter 7887319
 
20.9%
Space Separator 3869052
 
10.3%
Lowercase Letter 44582
 
0.1%
Dash Punctuation 22833
 
0.1%
Close Punctuation 41
 
< 0.1%
Open Punctuation 41
 
< 0.1%
Other Punctuation 16
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 42787
96.0%
r 208
 
0.5%
u 176
 
0.4%
a 170
 
0.4%
t 153
 
0.3%
b 150
 
0.3%
o 114
 
0.3%
p 109
 
0.2%
i 107
 
0.2%
m 105
 
0.2%
Other values (10) 503
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
S 3911382
49.6%
U 3911009
49.6%
D 39576
 
0.5%
A 24456
 
0.3%
E 382
 
< 0.1%
M 238
 
< 0.1%
P 144
 
< 0.1%
B 72
 
< 0.1%
L 48
 
< 0.1%
V 9
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 3434134
13.3%
1 3365755
13.0%
3 3065165
11.9%
5 2346706
9.1%
6 2337766
9.0%
4 2336936
9.0%
7 2291395
8.9%
0 2245737
8.7%
8 2221728
8.6%
9 2216894
8.6%
Other Punctuation
ValueCountFrequency (%)
? 9
56.2%
. 6
37.5%
' 1
 
6.2%
Space Separator
ValueCountFrequency (%)
3869052
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22833
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29754199
79.0%
Latin 7931901
 
21.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 3911382
49.3%
U 3911009
49.3%
w 42787
 
0.5%
D 39576
 
0.5%
A 24456
 
0.3%
E 382
 
< 0.1%
M 238
 
< 0.1%
r 208
 
< 0.1%
u 176
 
< 0.1%
a 170
 
< 0.1%
Other values (21) 1517
 
< 0.1%
Common
ValueCountFrequency (%)
3869052
13.0%
2 3434134
11.5%
1 3365755
11.3%
3 3065165
10.3%
5 2346706
7.9%
6 2337766
7.9%
4 2336936
7.9%
7 2291395
7.7%
0 2245737
7.5%
8 2221728
7.5%
Other values (7) 2239825
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37686100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 3911382
10.4%
U 3911009
10.4%
3869052
10.3%
2 3434134
9.1%
1 3365755
8.9%
3 3065165
8.1%
5 2346706
 
6.2%
6 2337766
 
6.2%
4 2336936
 
6.2%
7 2291395
 
6.1%
Other values (38) 6816800
18.1%

recordNumber
Text

Distinct483515
Distinct (%)10.8%
Missing39547
Missing (%)0.9%
Memory size34.5 MiB
2025-01-14T11:45:16.724239image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length100
Median length93
Mean length4.492128887
Min length1

Characters and Unicode

Total characters20107281
Distinct characters126
Distinct categories18 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique349259 ?
Unique (%)7.8%

Sample

1st rowBLM-210-IV-11-B-TDS
2nd row4319
3rd row2429
4th row95426
5th row1414/512
ValueCountFrequency (%)
s.n 643632
 
13.5%
bureau 20598
 
0.4%
eyd 15904
 
0.3%
s 14313
 
0.3%
of 13865
 
0.3%
n 13794
 
0.3%
science 13409
 
0.3%
d&ml 12897
 
0.3%
12506
 
0.3%
h 8672
 
0.2%
Other values (337587) 3987307
83.8%
2025-01-14T11:45:17.133242image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2407969
12.0%
2 1865104
9.3%
3 1606272
 
8.0%
4 1507264
 
7.5%
0 1450162
 
7.2%
5 1449381
 
7.2%
6 1399430
 
7.0%
. 1359512
 
6.8%
7 1317204
 
6.6%
8 1264749
 
6.3%
Other values (116) 4480234
22.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15496452
77.1%
Lowercase Letter 1833844
 
9.1%
Other Punctuation 1441238
 
7.2%
Uppercase Letter 729381
 
3.6%
Dash Punctuation 306820
 
1.5%
Space Separator 280783
 
1.4%
Open Punctuation 7886
 
< 0.1%
Close Punctuation 7869
 
< 0.1%
Other Number 1652
 
< 0.1%
Connector Punctuation 693
 
< 0.1%
Other values (8) 663
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 687647
37.5%
s 674180
36.8%
a 73396
 
4.0%
e 70280
 
3.8%
u 48891
 
2.7%
r 47050
 
2.6%
c 40273
 
2.2%
o 38076
 
2.1%
i 35764
 
2.0%
t 28937
 
1.6%
Other values (29) 89350
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
A 70745
 
9.7%
B 70158
 
9.6%
S 66805
 
9.2%
D 55914
 
7.7%
H 47763
 
6.5%
L 41753
 
5.7%
M 40705
 
5.6%
E 40361
 
5.5%
I 34875
 
4.8%
N 30792
 
4.2%
Other values (21) 229510
31.5%
Other Punctuation
ValueCountFrequency (%)
. 1359512
94.3%
& 24645
 
1.7%
/ 23862
 
1.7%
* 14056
 
1.0%
? 10512
 
0.7%
, 4971
 
0.3%
! 2281
 
0.2%
# 372
 
< 0.1%
: 371
 
< 0.1%
; 329
 
< 0.1%
Other values (6) 327
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 2407969
15.5%
2 1865104
12.0%
3 1606272
10.4%
4 1507264
9.7%
0 1450162
9.4%
5 1449381
9.4%
6 1399430
9.0%
7 1317204
8.5%
8 1264749
8.2%
9 1228917
7.9%
Other Number
ValueCountFrequency (%)
½ 1595
96.5%
² 21
 
1.3%
¼ 17
 
1.0%
¾ 6
 
0.4%
⅓ 5
 
0.3%
³ 5
 
0.3%
⁴ 1
 
0.1%
⅔ 1
 
0.1%
¹ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
= 510
78.7%
+ 133
 
20.5%
~ 4
 
0.6%
± 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 7214
91.5%
[ 424
 
5.4%
{ 248
 
3.1%
Close Punctuation
ValueCountFrequency (%)
) 7198
91.5%
] 423
 
5.4%
} 248
 
3.2%
Other Letter
ValueCountFrequency (%)
ª 2
66.7%
º 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 306820
100.0%
Space Separator
ValueCountFrequency (%)
280783
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 693
100.0%
Final Punctuation
ValueCountFrequency (%)
› 6
100.0%
Modifier Letter
ValueCountFrequency (%)
ˍ 2
100.0%
Control
ValueCountFrequency (%)
 1
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 1
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17544053
87.3%
Latin 2563226
 
12.7%
Greek 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 687647
26.8%
s 674180
26.3%
a 73396
 
2.9%
A 70745
 
2.8%
e 70280
 
2.7%
B 70158
 
2.7%
S 66805
 
2.6%
D 55914
 
2.2%
u 48891
 
1.9%
H 47763
 
1.9%
Other values (61) 697447
27.2%
Common
ValueCountFrequency (%)
1 2407969
13.7%
2 1865104
10.6%
3 1606272
9.2%
4 1507264
8.6%
0 1450162
8.3%
5 1449381
8.3%
6 1399430
8.0%
. 1359512
7.7%
7 1317204
7.5%
8 1264749
7.2%
Other values (44) 1917006
10.9%
Greek
ValueCountFrequency (%)
Σ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20105496
> 99.9%
None 1767
 
< 0.1%
Punctuation 10
 
< 0.1%
Number Forms 6
 
< 0.1%
Modifier Letters 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2407969
12.0%
2 1865104
9.3%
3 1606272
 
8.0%
4 1507264
 
7.5%
0 1450162
 
7.2%
5 1449381
 
7.2%
6 1399430
 
7.0%
. 1359512
 
6.8%
7 1317204
 
6.6%
8 1264749
 
6.3%
Other values (80) 4478449
22.3%
None
ValueCountFrequency (%)
½ 1595
90.3%
è 47
 
2.7%
² 21
 
1.2%
¼ 17
 
1.0%
ß 12
 
0.7%
é 11
 
0.6%
á 9
 
0.5%
ó 7
 
0.4%
¾ 6
 
0.3%
ü 5
 
0.3%
Other values (21) 37
 
2.1%
Punctuation
ValueCountFrequency (%)
› 6
60.0%
… 4
40.0%
Number Forms
ValueCountFrequency (%)
⅓ 5
83.3%
⅔ 1
 
16.7%
Modifier Letters
ValueCountFrequency (%)
ˍ 2
100.0%

recordedBy
Text

Missing 

Distinct148160
Distinct (%)3.3%
Missing54378
Missing (%)1.2%
Memory size34.5 MiB
2025-01-14T11:45:17.344841image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length207
Median length182
Mean length17.24845678
Min length1

Characters and Unicode

Total characters76950247
Distinct characters169
Distinct categories15 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68031 ?
Unique (%)1.5%

Sample

1st rowContinental Shelf Associates for the MMS/BLM
2nd rowJ. Soukup
3rd rowI. Morel
4th rowJ. Steyermark & Cora Steyermark
5th rowA. Oakes & -. Ellis
ValueCountFrequency (%)
1250739
 
7.3%
j 893043
 
5.2%
a 765542
 
4.5%
r 679021
 
4.0%
e 678845
 
4.0%
c 633969
 
3.7%
m 612375
 
3.6%
h 550473
 
3.2%
l 447598
 
2.6%
w 441682
 
2.6%
Other values (47910) 10064443
59.1%
2025-01-14T11:45:17.635673image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12556447
16.3%
. 9149950
 
11.9%
e 4946918
 
6.4%
r 3620522
 
4.7%
a 3597020
 
4.7%
o 3035449
 
3.9%
n 3020373
 
3.9%
l 2882126
 
3.7%
i 2489174
 
3.2%
t 2009722
 
2.6%
Other values (159) 29642546
38.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 37329688
48.5%
Uppercase Letter 15658675
20.3%
Space Separator 12556447
 
16.3%
Other Punctuation 11032380
 
14.3%
Dash Punctuation 338372
 
0.4%
Decimal Number 13770
 
< 0.1%
Open Punctuation 10381
 
< 0.1%
Close Punctuation 10377
 
< 0.1%
Math Symbol 95
 
< 0.1%
Modifier Symbol 37
 
< 0.1%
Other values (5) 25
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4946918
13.3%
r 3620522
9.7%
a 3597020
9.6%
o 3035449
 
8.1%
n 3020373
 
8.1%
l 2882126
 
7.7%
i 2489174
 
6.7%
t 2009722
 
5.4%
s 1900211
 
5.1%
u 1165862
 
3.1%
Other values (72) 8662311
23.2%
Uppercase Letter
ValueCountFrequency (%)
C 1201916
 
7.7%
S 1183226
 
7.6%
M 1107889
 
7.1%
R 1107469
 
7.1%
H 1091576
 
7.0%
A 1069398
 
6.8%
J 1064721
 
6.8%
E 869534
 
5.6%
B 829485
 
5.3%
L 808858
 
5.2%
Other values (37) 5324603
34.0%
Other Punctuation
ValueCountFrequency (%)
. 9149950
82.9%
& 1104307
 
10.0%
, 759260
 
6.9%
' 13249
 
0.1%
/ 3911
 
< 0.1%
" 1654
 
< 0.1%
; 19
 
< 0.1%
? 17
 
< 0.1%
¡ 5
 
< 0.1%
: 3
 
< 0.1%
Other values (4) 5
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
8 2642
19.2%
1 2372
17.2%
9 2198
16.0%
0 2008
14.6%
3 1492
10.8%
4 1264
9.2%
5 1196
8.7%
2 395
 
2.9%
7 191
 
1.4%
6 12
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 10272
99.0%
[ 108
 
1.0%
‚ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 10270
99.0%
] 107
 
1.0%
Math Symbol
ValueCountFrequency (%)
= 93
97.9%
+ 2
 
2.1%
Control
ValueCountFrequency (%)
 1
50.0%
 1
50.0%
Space Separator
ValueCountFrequency (%)
12556447
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 338372
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 37
100.0%
Other Symbol
ValueCountFrequency (%)
° 14
100.0%
Final Punctuation
ValueCountFrequency (%)
» 4
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 4
100.0%
Currency Symbol
ValueCountFrequency (%)
¢ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 52988360
68.9%
Common 23961884
31.1%
Cyrillic 2
 
< 0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4946918
 
9.3%
r 3620522
 
6.8%
a 3597020
 
6.8%
o 3035449
 
5.7%
n 3020373
 
5.7%
l 2882126
 
5.4%
i 2489174
 
4.7%
t 2009722
 
3.8%
s 1900211
 
3.6%
C 1201916
 
2.3%
Other values (117) 24284929
45.8%
Common
ValueCountFrequency (%)
12556447
52.4%
. 9149950
38.2%
& 1104307
 
4.6%
, 759260
 
3.2%
- 338372
 
1.4%
' 13249
 
0.1%
( 10272
 
< 0.1%
) 10270
 
< 0.1%
/ 3911
 
< 0.1%
8 2642
 
< 0.1%
Other values (30) 13204
 
0.1%
Cyrillic
ValueCountFrequency (%)
Ӧ 2
100.0%
Greek
ValueCountFrequency (%)
β 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76700430
99.7%
None 249806
 
0.3%
IPA Ext 8
 
< 0.1%
Cyrillic 2
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12556447
16.4%
. 9149950
 
11.9%
e 4946918
 
6.4%
r 3620522
 
4.7%
a 3597020
 
4.7%
o 3035449
 
4.0%
n 3020373
 
3.9%
l 2882126
 
3.8%
i 2489174
 
3.2%
t 2009722
 
2.6%
Other values (72) 29392729
38.3%
None
ValueCountFrequency (%)
á 42487
17.0%
é 42189
16.9%
ó 38921
15.6%
í 28776
11.5%
ñ 24979
10.0%
è 17057
6.8%
ü 13598
 
5.4%
ö 10723
 
4.3%
ê 6878
 
2.8%
ç 3147
 
1.3%
Other values (74) 21051
8.4%
IPA Ext
ValueCountFrequency (%)
ɶ 8
100.0%
Cyrillic
ValueCountFrequency (%)
Ӧ 2
100.0%
Punctuation
ValueCountFrequency (%)
‚ 1
100.0%

individualCount
Text

Distinct22
Distinct (%)< 0.1%
Missing560
Missing (%)< 0.1%
Memory size34.5 MiB
2025-01-14T11:45:17.704168image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.000007973
Min length1

Characters and Unicode

Total characters4515137
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 4513894
> 99.9%
2 489
 
< 0.1%
0 306
 
< 0.1%
3 137
 
< 0.1%
4 94
 
< 0.1%
5 55
 
< 0.1%
6 40
 
< 0.1%
7 21
 
< 0.1%
8 16
 
< 0.1%
9 13
 
< 0.1%
Other values (12) 36
 
< 0.1%
2025-01-14T11:45:17.816292image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4513935
> 99.9%
2 496
 
< 0.1%
0 315
 
< 0.1%
3 142
 
< 0.1%
4 96
 
< 0.1%
5 57
 
< 0.1%
6 42
 
< 0.1%
7 22
 
< 0.1%
8 17
 
< 0.1%
9 15
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4515137
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4513935
> 99.9%
2 496
 
< 0.1%
0 315
 
< 0.1%
3 142
 
< 0.1%
4 96
 
< 0.1%
5 57
 
< 0.1%
6 42
 
< 0.1%
7 22
 
< 0.1%
8 17
 
< 0.1%
9 15
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 4515137
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4513935
> 99.9%
2 496
 
< 0.1%
0 315
 
< 0.1%
3 142
 
< 0.1%
4 96
 
< 0.1%
5 57
 
< 0.1%
6 42
 
< 0.1%
7 22
 
< 0.1%
8 17
 
< 0.1%
9 15
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4515137
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4513935
> 99.9%
2 496
 
< 0.1%
0 315
 
< 0.1%
3 142
 
< 0.1%
4 96
 
< 0.1%
5 57
 
< 0.1%
6 42
 
< 0.1%
7 22
 
< 0.1%
8 17
 
< 0.1%
9 15
 
< 0.1%

lifeStage
Text

Missing 

Distinct117
Distinct (%)< 0.1%
Missing4152582
Missing (%)92.0%
Memory size34.5 MiB
2025-01-14T11:45:17.878806image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length60
Median length9
Mean length10.22810187
Min length1

Characters and Unicode

Total characters3713609
Distinct characters44
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)< 0.1%

Sample

1st rowFruiting
2nd rowIn bud
3rd rowFlowering
4th rowFlowering
5th rowImmature fruit
ValueCountFrequency (%)
flowering 233588
50.4%
fruiting 101100
21.8%
and 42692
 
9.2%
vegetative 23865
 
5.1%
fertile 18492
 
4.0%
in 8662
 
1.9%
bud 8099
 
1.7%
flower 7510
 
1.6%
fruit 7391
 
1.6%
sterile 3316
 
0.7%
Other values (52) 9209
 
2.0%
2025-01-14T11:45:18.009707image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 489124
13.2%
n 386365
10.4%
r 377645
10.2%
e 366016
9.9%
g 358832
9.7%
F 358692
9.7%
l 267441
7.2%
o 243782
6.6%
w 243567
6.6%
t 181837
 
4.9%
Other values (34) 440308
11.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3213326
86.5%
Uppercase Letter 398816
 
10.7%
Space Separator 100845
 
2.7%
Other Punctuation 608
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 489124
15.2%
n 386365
12.0%
r 377645
11.8%
e 366016
11.4%
g 358832
11.2%
l 267441
8.3%
o 243782
7.6%
w 243567
7.6%
t 181837
 
5.7%
u 120719
 
3.8%
Other values (13) 177998
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
F 358692
89.9%
V 23712
 
5.9%
I 10944
 
2.7%
S 3091
 
0.8%
M 1845
 
0.5%
B 367
 
0.1%
Y 156
 
< 0.1%
C 3
 
< 0.1%
P 3
 
< 0.1%
J 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
? 330
54.3%
& 178
29.3%
; 52
 
8.6%
. 30
 
4.9%
, 18
 
3.0%
Close Punctuation
ValueCountFrequency (%)
] 6
85.7%
) 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
[ 6
85.7%
( 1
 
14.3%
Space Separator
ValueCountFrequency (%)
100845
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3612142
97.3%
Common 101467
 
2.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 489124
13.5%
n 386365
10.7%
r 377645
10.5%
e 366016
10.1%
g 358832
9.9%
F 358692
9.9%
l 267441
7.4%
o 243782
6.7%
w 243567
6.7%
t 181837
 
5.0%
Other values (24) 338841
9.4%
Common
ValueCountFrequency (%)
100845
99.4%
? 330
 
0.3%
& 178
 
0.2%
; 52
 
0.1%
. 30
 
< 0.1%
, 18
 
< 0.1%
] 6
 
< 0.1%
[ 6
 
< 0.1%
( 1
 
< 0.1%
) 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3713599
> 99.9%
None 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 489124
13.2%
n 386365
10.4%
r 377645
10.2%
e 366016
9.9%
g 358832
9.7%
F 358692
9.7%
l 267441
7.2%
o 243782
6.6%
w 243567
6.6%
t 181837
 
4.9%
Other values (33) 440298
11.9%
None
ValueCountFrequency (%)
í 10
100.0%

preparations
Text

Missing 

Distinct117
Distinct (%)0.1%
Missing4381212
Missing (%)97.0%
Memory size34.5 MiB
2025-01-14T11:45:18.080765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length154
Median length142
Mean length13.21074906
Min length3

Characters and Unicode

Total characters1776172
Distinct characters55
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)< 0.1%

Sample

1st rowWood Sample
2nd rowPhotograph
3rd rowMicroslide
4th rowPhotograph
5th rowPhotograph; Photograph
ValueCountFrequency (%)
sample 42484
18.8%
wood 42481
18.8%
microslide 41833
18.5%
photograph 33523
14.8%
individual 18796
8.3%
strewn 10233
 
4.5%
sem 6926
 
3.1%
micrograph 6518
 
2.9%
ink 5466
 
2.4%
and 3022
 
1.3%
Other values (80) 15061
 
6.7%
2025-01-14T11:45:18.238819image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 203882
 
11.5%
i 158041
 
8.9%
d 125573
 
7.1%
l 110697
 
6.2%
a 110082
 
6.2%
r 106206
 
6.0%
e 101621
 
5.7%
91894
 
5.2%
p 85868
 
4.8%
h 73865
 
4.2%
Other values (45) 608443
34.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1435215
80.8%
Uppercase Letter 188766
 
10.6%
Space Separator 91894
 
5.2%
Open Punctuation 29029
 
1.6%
Close Punctuation 29029
 
1.6%
Other Punctuation 2234
 
0.1%
Decimal Number 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 203882
14.2%
i 158041
11.0%
d 125573
8.7%
l 110697
 
7.7%
a 110082
 
7.7%
r 106206
 
7.4%
e 101621
 
7.1%
p 85868
 
6.0%
h 73865
 
5.1%
s 53207
 
3.7%
Other values (16) 306173
21.3%
Uppercase Letter
ValueCountFrequency (%)
S 49907
26.4%
M 48777
25.8%
W 43261
22.9%
P 33419
17.7%
E 7153
 
3.8%
B 2795
 
1.5%
I 2467
 
1.3%
F 648
 
0.3%
D 226
 
0.1%
T 77
 
< 0.1%
Other values (9) 36
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 2
40.0%
5 1
20.0%
2 1
20.0%
6 1
20.0%
Other Punctuation
ValueCountFrequency (%)
; 2198
98.4%
, 35
 
1.6%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
91894
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29029
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29029
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1623981
91.4%
Common 152191
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 203882
12.6%
i 158041
 
9.7%
d 125573
 
7.7%
l 110697
 
6.8%
a 110082
 
6.8%
r 106206
 
6.5%
e 101621
 
6.3%
p 85868
 
5.3%
h 73865
 
4.5%
s 53207
 
3.3%
Other values (35) 494939
30.5%
Common
ValueCountFrequency (%)
91894
60.4%
( 29029
 
19.1%
) 29029
 
19.1%
; 2198
 
1.4%
, 35
 
< 0.1%
0 2
 
< 0.1%
& 1
 
< 0.1%
5 1
 
< 0.1%
2 1
 
< 0.1%
6 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1776172
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 203882
 
11.5%
i 158041
 
8.9%
d 125573
 
7.1%
l 110697
 
6.2%
a 110082
 
6.2%
r 106206
 
6.0%
e 101621
 
5.7%
91894
 
5.2%
p 85868
 
4.8%
h 73865
 
4.2%
Other values (45) 608443
34.3%

associatedMedia
Text

Missing 

Distinct4172762
Distinct (%)99.4%
Missing318147
Missing (%)7.0%
Memory size34.5 MiB
2025-01-14T11:45:20.719113image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1040
Median length49
Mean length49.74545934
Min length48

Characters and Unicode

Total characters208807262
Distinct characters31
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4151953 ?
Unique (%)98.9%

Sample

1st rowhttps://collections.nmnh.si.edu/media/?i=12410529
2nd rowhttps://collections.nmnh.si.edu/media/?i=14440219
3rd rowhttps://collections.nmnh.si.edu/media/?i=14306337
4th rowhttps://collections.nmnh.si.edu/media/?i=15522674
5th rowhttps://collections.nmnh.si.edu/media/?i=15293772
ValueCountFrequency (%)
16574494 50
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=13965384 42
 
< 0.1%
16580564 35
 
< 0.1%
16582219 30
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=15413125 25
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=16645032 22
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=15413478 21
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=10422983 19
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=15921416 17
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=16645082 16
 
< 0.1%
Other values (4474099) 4510811
> 99.9%
2025-01-14T11:45:23.377450image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 16790056
 
8.0%
i 16790056
 
8.0%
s 12592542
 
6.0%
e 12592542
 
6.0%
n 12592542
 
6.0%
. 12592542
 
6.0%
t 12592542
 
6.0%
h 8395028
 
4.0%
c 8395028
 
4.0%
o 8395028
 
4.0%
Other values (21) 87079356
41.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 130122934
62.3%
Other Punctuation 38091203
 
18.2%
Decimal Number 36082037
 
17.3%
Math Symbol 4197514
 
2.0%
Space Separator 313574
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 16790056
12.9%
s 12592542
9.7%
e 12592542
9.7%
n 12592542
9.7%
t 12592542
9.7%
h 8395028
 
6.5%
c 8395028
 
6.5%
o 8395028
 
6.5%
l 8395028
 
6.5%
m 8395028
 
6.5%
Other values (4) 20987570
16.1%
Decimal Number
ValueCountFrequency (%)
1 8143819
22.6%
2 3518459
9.8%
5 3514642
9.7%
3 3509019
9.7%
4 3458224
9.6%
0 3078625
 
8.5%
6 3018330
 
8.4%
9 2670129
 
7.4%
7 2613317
 
7.2%
8 2557473
 
7.1%
Other Punctuation
ValueCountFrequency (%)
/ 16790056
44.1%
. 12592542
33.1%
? 4197514
 
11.0%
: 4197514
 
11.0%
; 313577
 
0.8%
Math Symbol
ValueCountFrequency (%)
= 4197514
100.0%
Space Separator
ValueCountFrequency (%)
313574
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 130122934
62.3%
Common 78684328
37.7%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 16790056
21.3%
. 12592542
16.0%
1 8143819
10.3%
? 4197514
 
5.3%
= 4197514
 
5.3%
: 4197514
 
5.3%
2 3518459
 
4.5%
5 3514642
 
4.5%
3 3509019
 
4.5%
4 3458224
 
4.4%
Other values (7) 14565025
18.5%
Latin
ValueCountFrequency (%)
i 16790056
12.9%
s 12592542
9.7%
e 12592542
9.7%
n 12592542
9.7%
t 12592542
9.7%
h 8395028
 
6.5%
c 8395028
 
6.5%
o 8395028
 
6.5%
l 8395028
 
6.5%
m 8395028
 
6.5%
Other values (4) 20987570
16.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 208807262
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 16790056
 
8.0%
i 16790056
 
8.0%
s 12592542
 
6.0%
e 12592542
 
6.0%
n 12592542
 
6.0%
. 12592542
 
6.0%
t 12592542
 
6.0%
h 8395028
 
4.0%
c 8395028
 
4.0%
o 8395028
 
4.0%
Other values (21) 87079356
41.7%

associatedSequences
Text

Missing 

Distinct334
Distinct (%)95.2%
Missing4515310
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:23.469344image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length499
Median length249
Mean length140.8803419
Min length49

Characters and Unicode

Total characters49449
Distinct characters50
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique317 ?
Unique (%)90.3%

Sample

1st rowhttps://www.ncbi.nlm.nih.gov/gquery?term=ON553270
2nd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=MT553291
3rd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=MT553246
4th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=MT553283
5th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=EU527211|https://www.ncbi.nlm.nih.gov/gquery?term=EU527308|https://www.ncbi.nlm.nih.gov/gquery?term=EU527261
ValueCountFrequency (%)
https://www.ncbi.nlm.nih.gov/gquery?term=jn837179|https://www.ncbi.nlm.nih.gov/gquery?term=jn837463|https://www.ncbi.nlm.nih.gov/gquery?term=jn837359|https://www.ncbi.nlm.nih.gov/gquery?term=jn837269 2
 
0.6%
https://www.ncbi.nlm.nih.gov/gquery?term=jn837192|https://www.ncbi.nlm.nih.gov/gquery?term=jn837282|https://www.ncbi.nlm.nih.gov/gquery?term=jn837372|https://www.ncbi.nlm.nih.gov/gquery?term=jn837475 2
 
0.6%
https://www.ncbi.nlm.nih.gov/gquery?term=eu527212|https://www.ncbi.nlm.nih.gov/gquery?term=eu527309|https://www.ncbi.nlm.nih.gov/gquery?term=eu527262 2
 
0.6%
https://www.ncbi.nlm.nih.gov/gquery?term=jn837150|https://www.ncbi.nlm.nih.gov/gquery?term=jn837436|https://www.ncbi.nlm.nih.gov/gquery?term=jn837330|https://www.ncbi.nlm.nih.gov/gquery?term=jn837240 2
 
0.6%
https://www.ncbi.nlm.nih.gov/gquery?term=jn837187|https://www.ncbi.nlm.nih.gov/gquery?term=jn837470|https://www.ncbi.nlm.nih.gov/gquery?term=jn837367|https://www.ncbi.nlm.nih.gov/gquery?term=jn837277 2
 
0.6%
https://www.ncbi.nlm.nih.gov/gquery?term=kf989555|https://www.ncbi.nlm.nih.gov/gquery?term=kf989872|https://www.ncbi.nlm.nih.gov/gquery?term=kf989774|https://www.ncbi.nlm.nih.gov/gquery?term=kf989974|https://www.ncbi.nlm.nih.gov/gquery?term=kf989663 2
 
0.6%
https://www.ncbi.nlm.nih.gov/gquery?term=jn837109|https://www.ncbi.nlm.nih.gov/gquery?term=jn837391|https://www.ncbi.nlm.nih.gov/gquery?term=jn837290|https://www.ncbi.nlm.nih.gov/gquery?term=jn837199 2
 
0.6%
https://www.ncbi.nlm.nih.gov/gquery?term=eu527241|https://www.ncbi.nlm.nih.gov/gquery?term=eu527291 2
 
0.6%
https://www.ncbi.nlm.nih.gov/gquery?term=jn837183|https://www.ncbi.nlm.nih.gov/gquery?term=jn837467|https://www.ncbi.nlm.nih.gov/gquery?term=jn837363|https://www.ncbi.nlm.nih.gov/gquery?term=jn837273 2
 
0.6%
https://www.ncbi.nlm.nih.gov/gquery?term=jn837191|https://www.ncbi.nlm.nih.gov/gquery?term=jn837281|https://www.ncbi.nlm.nih.gov/gquery?term=jn837371|https://www.ncbi.nlm.nih.gov/gquery?term=jn837474 2
 
0.6%
Other values (324) 331
94.3%
2025-01-14T11:45:23.610913image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 3984
 
8.1%
t 2988
 
6.0%
/ 2988
 
6.0%
w 2988
 
6.0%
n 2988
 
6.0%
h 1992
 
4.0%
i 1992
 
4.0%
r 1992
 
4.0%
m 1992
 
4.0%
g 1992
 
4.0%
Other values (40) 23553
47.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 30876
62.4%
Other Punctuation 8964
 
18.1%
Decimal Number 5976
 
12.1%
Uppercase Letter 1992
 
4.0%
Math Symbol 1641
 
3.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2988
 
9.7%
w 2988
 
9.7%
n 2988
 
9.7%
h 1992
 
6.5%
i 1992
 
6.5%
r 1992
 
6.5%
m 1992
 
6.5%
g 1992
 
6.5%
e 1992
 
6.5%
u 996
 
3.2%
Other values (9) 8964
29.0%
Uppercase Letter
ValueCountFrequency (%)
K 384
19.3%
F 380
19.1%
N 338
17.0%
J 302
15.2%
M 96
 
4.8%
E 94
 
4.7%
U 94
 
4.7%
T 91
 
4.6%
Y 57
 
2.9%
A 54
 
2.7%
Other values (5) 102
 
5.1%
Decimal Number
ValueCountFrequency (%)
9 1075
18.0%
8 963
16.1%
3 756
12.7%
7 724
12.1%
5 679
11.4%
2 540
9.0%
0 349
 
5.8%
4 308
 
5.2%
6 296
 
5.0%
1 286
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 3984
44.4%
/ 2988
33.3%
? 996
 
11.1%
: 996
 
11.1%
Math Symbol
ValueCountFrequency (%)
= 996
60.7%
| 645
39.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 32868
66.5%
Common 16581
33.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2988
 
9.1%
w 2988
 
9.1%
n 2988
 
9.1%
h 1992
 
6.1%
i 1992
 
6.1%
r 1992
 
6.1%
m 1992
 
6.1%
g 1992
 
6.1%
e 1992
 
6.1%
u 996
 
3.0%
Other values (24) 10956
33.3%
Common
ValueCountFrequency (%)
. 3984
24.0%
/ 2988
18.0%
9 1075
 
6.5%
= 996
 
6.0%
? 996
 
6.0%
: 996
 
6.0%
8 963
 
5.8%
3 756
 
4.6%
7 724
 
4.4%
5 679
 
4.1%
Other values (6) 2424
14.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49449
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 3984
 
8.1%
t 2988
 
6.0%
/ 2988
 
6.0%
w 2988
 
6.0%
n 2988
 
6.0%
h 1992
 
4.0%
i 1992
 
4.0%
r 1992
 
4.0%
m 1992
 
4.0%
g 1992
 
4.0%
Other values (40) 23553
47.6%

occurrenceRemarks
Text

Missing 

Distinct28685
Distinct (%)31.3%
Missing4424129
Missing (%)98.0%
Memory size34.5 MiB
2025-01-14T11:45:23.810693image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length54951
Median length2489
Mean length77.45450771
Min length1

Characters and Unicode

Total characters7089566
Distinct characters143
Distinct categories19 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24536 ?
Unique (%)26.8%

Sample

1st rowReceived as: seed
2nd rowTranscribed by digital volunteers
3rd rowBRG
4th rowTranscribed by digital volunteers; Original spelling as annotated and published is "subplebeia". Same (?) taxon re-published in Contr. U.S. Natl. Herb. 17: 46 (1913) with more explicit type citation. Unclear whether Lecidea subplebeia is a later homonym of Lecidea subplebeja Vain. (1890); Lecidea austrocalifornica Zahlbr. published as replacement name but citing Lecidea "subplebeja Nyl. apud Hasse". The latter name is superfluous if the original name is not a later homonym.
5th rowUS, NY
ValueCountFrequency (%)
by 38261
 
3.8%
transcribed 30348
 
3.0%
digital 30037
 
2.9%
volunteers 30020
 
2.9%
19663
 
1.9%
of 17327
 
1.7%
us 14702
 
1.4%
as 13939
 
1.4%
and 12959
 
1.3%
the 12017
 
1.2%
Other values (45812) 799986
78.5%
2025-01-14T11:45:24.103445image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
923590
 
13.0%
e 568137
 
8.0%
a 443985
 
6.3%
i 409730
 
5.8%
t 348936
 
4.9%
n 338603
 
4.8%
o 337481
 
4.8%
r 330807
 
4.7%
l 294956
 
4.2%
s 270029
 
3.8%
Other values (133) 2823312
39.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4729210
66.7%
Space Separator 923590
 
13.0%
Uppercase Letter 609062
 
8.6%
Other Punctuation 376914
 
5.3%
Decimal Number 324218
 
4.6%
Dash Punctuation 37930
 
0.5%
Open Punctuation 31537
 
0.4%
Close Punctuation 31514
 
0.4%
Control 22926
 
0.3%
Connector Punctuation 867
 
< 0.1%
Other values (9) 1798
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 568137
12.0%
a 443985
 
9.4%
i 409730
 
8.7%
t 348936
 
7.4%
n 338603
 
7.2%
o 337481
 
7.1%
r 330807
 
7.0%
l 294956
 
6.2%
s 270029
 
5.7%
c 199665
 
4.2%
Other values (38) 1186881
25.1%
Uppercase Letter
ValueCountFrequency (%)
S 64247
 
10.5%
T 55830
 
9.2%
C 52060
 
8.5%
A 46853
 
7.7%
B 38326
 
6.3%
P 32445
 
5.3%
F 29814
 
4.9%
R 27321
 
4.5%
H 26318
 
4.3%
M 25872
 
4.2%
Other values (21) 209976
34.5%
Other Punctuation
ValueCountFrequency (%)
. 162150
43.0%
, 110035
29.2%
; 39470
 
10.5%
: 28446
 
7.5%
" 18510
 
4.9%
& 7482
 
2.0%
' 4679
 
1.2%
/ 3130
 
0.8%
? 1562
 
0.4%
# 885
 
0.2%
Other values (8) 565
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 71150
21.9%
9 44064
13.6%
2 35632
11.0%
0 33874
10.4%
3 26448
 
8.2%
8 25545
 
7.9%
4 23422
 
7.2%
5 22222
 
6.9%
7 22144
 
6.8%
6 19717
 
6.1%
Math Symbol
ValueCountFrequency (%)
= 639
74.3%
+ 137
 
15.9%
× 58
 
6.7%
~ 12
 
1.4%
> 5
 
0.6%
± 4
 
0.5%
< 3
 
0.3%
¬ 1
 
0.1%
| 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 37484
98.8%
– 440
 
1.2%
— 5
 
< 0.1%
‒ 1
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
° 98
81.7%
© 17
 
14.2%
♂ 4
 
3.3%
® 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 29639
94.0%
[ 1894
 
6.0%
{ 4
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 29625
94.0%
] 1887
 
6.0%
} 2
 
< 0.1%
Nonspacing Mark
ValueCountFrequency (%)
́ 309
60.0%
̧ 103
 
20.0%
̀ 103
 
20.0%
Control
ValueCountFrequency (%)
22806
99.5%
120
 
0.5%
Space Separator
ValueCountFrequency (%)
923590
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 867
100.0%
Final Punctuation
ValueCountFrequency (%)
” 148
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 142
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 7
100.0%
Other Letter
ValueCountFrequency (%)
º 4
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%
Other Number
ValueCountFrequency (%)
½ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5338276
75.3%
Common 1750775
 
24.7%
Inherited 515
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 568137
 
10.6%
a 443985
 
8.3%
i 409730
 
7.7%
t 348936
 
6.5%
n 338603
 
6.3%
o 337481
 
6.3%
r 330807
 
6.2%
l 294956
 
5.5%
s 270029
 
5.1%
c 199665
 
3.7%
Other values (70) 1795947
33.6%
Common
ValueCountFrequency (%)
923590
52.8%
. 162150
 
9.3%
, 110035
 
6.3%
1 71150
 
4.1%
9 44064
 
2.5%
; 39470
 
2.3%
- 37484
 
2.1%
2 35632
 
2.0%
0 33874
 
1.9%
( 29639
 
1.7%
Other values (50) 263687
 
15.1%
Inherited
ValueCountFrequency (%)
́ 309
60.0%
̧ 103
 
20.0%
̀ 103
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7085628
99.9%
None 2622
 
< 0.1%
Punctuation 797
 
< 0.1%
Diacriticals 515
 
< 0.1%
Misc Symbols 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
923590
 
13.0%
e 568137
 
8.0%
a 443985
 
6.3%
i 409730
 
5.8%
t 348936
 
4.9%
n 338603
 
4.8%
o 337481
 
4.8%
r 330807
 
4.7%
l 294956
 
4.2%
s 270029
 
3.8%
Other values (85) 2819374
39.8%
None
ValueCountFrequency (%)
í 836
31.9%
é 406
15.5%
ñ 338
12.9%
á 275
 
10.5%
ó 130
 
5.0%
° 98
 
3.7%
ç 87
 
3.3%
è 79
 
3.0%
ü 69
 
2.6%
ö 61
 
2.3%
Other values (27) 243
 
9.3%
Punctuation
ValueCountFrequency (%)
– 440
55.2%
” 148
 
18.6%
“ 142
 
17.8%
• 48
 
6.0%
… 13
 
1.6%
— 5
 
0.6%
‒ 1
 
0.1%
Diacriticals
ValueCountFrequency (%)
́ 309
60.0%
̧ 103
 
20.0%
̀ 103
 
20.0%
Misc Symbols
ValueCountFrequency (%)
♂ 4
100.0%

organismName
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing4515658
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:24.162889image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.666666667
Min length5

Characters and Unicode

Total characters17
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row3018.0
2nd row300.0
3rd row1580.0
ValueCountFrequency (%)
3018.0 1
33.3%
300.0 1
33.3%
1580.0 1
33.3%
2025-01-14T11:45:24.260701image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7
41.2%
. 3
17.6%
3 2
 
11.8%
1 2
 
11.8%
8 2
 
11.8%
5 1
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
82.4%
Other Punctuation 3
 
17.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7
50.0%
3 2
 
14.3%
1 2
 
14.3%
8 2
 
14.3%
5 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7
41.2%
. 3
17.6%
3 2
 
11.8%
1 2
 
11.8%
8 2
 
11.8%
5 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7
41.2%
. 3
17.6%
3 2
 
11.8%
1 2
 
11.8%
8 2
 
11.8%
5 1
 
5.9%

eventType
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing4515660
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:24.305545image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row-7.38
ValueCountFrequency (%)
7.38 1
100.0%
2025-01-14T11:45:24.396661image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1
20.0%
7 1
20.0%
. 1
20.0%
3 1
20.0%
8 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
60.0%
Dash Punctuation 1
 
20.0%
Other Punctuation 1
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 1
33.3%
3 1
33.3%
8 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1
20.0%
7 1
20.0%
. 1
20.0%
3 1
20.0%
8 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1
20.0%
7 1
20.0%
. 1
20.0%
3 1
20.0%
8 1
20.0%

fieldNumber
Text

Missing 

Distinct15
Distinct (%)5.7%
Missing4515399
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:24.454247image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length9
Mean length9.122137405
Min length4

Characters and Unicode

Total characters2390
Distinct characters44
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)3.1%

Sample

1st rowSample OY
2nd rowSample OY
3rd rowSample OY
4th rowSample OY
5th rowSample OY
ValueCountFrequency (%)
sample 240
46.1%
oy 240
46.1%
koolau 5
 
1.0%
b 4
 
0.8%
a 4
 
0.8%
259 3
 
0.6%
l-52 3
 
0.6%
koolau_784 3
 
0.6%
17-v-88-5-n 2
 
0.4%
zeeland 2
 
0.4%
Other values (13) 15
 
2.9%
2025-01-14T11:45:24.579176image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 263
11.0%
259
10.8%
l 255
10.7%
e 247
10.3%
S 241
10.1%
p 240
10.0%
m 240
10.0%
O 240
10.0%
Y 240
10.0%
o 19
 
0.8%
Other values (34) 146
6.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1302
54.5%
Uppercase Letter 750
31.4%
Space Separator 259
 
10.8%
Decimal Number 57
 
2.4%
Dash Punctuation 12
 
0.5%
Connector Punctuation 7
 
0.3%
Other Punctuation 3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 263
20.2%
l 255
19.6%
e 247
19.0%
p 240
18.4%
m 240
18.4%
o 19
 
1.5%
u 9
 
0.7%
n 7
 
0.5%
i 5
 
0.4%
b 4
 
0.3%
Other values (7) 13
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
S 241
32.1%
O 240
32.0%
Y 240
32.0%
K 9
 
1.2%
B 4
 
0.5%
A 3
 
0.4%
L 3
 
0.4%
V 3
 
0.4%
Z 2
 
0.3%
H 2
 
0.3%
Other values (3) 3
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 11
19.3%
5 11
19.3%
8 10
17.5%
1 6
10.5%
7 5
8.8%
4 5
8.8%
0 4
 
7.0%
9 3
 
5.3%
3 1
 
1.8%
6 1
 
1.8%
Space Separator
ValueCountFrequency (%)
259
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2052
85.9%
Common 338
 
14.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 263
12.8%
l 255
12.4%
e 247
12.0%
S 241
11.7%
p 240
11.7%
m 240
11.7%
O 240
11.7%
Y 240
11.7%
o 19
 
0.9%
u 9
 
0.4%
Other values (20) 58
 
2.8%
Common
ValueCountFrequency (%)
259
76.6%
- 12
 
3.6%
2 11
 
3.3%
5 11
 
3.3%
8 10
 
3.0%
_ 7
 
2.1%
1 6
 
1.8%
7 5
 
1.5%
4 5
 
1.5%
0 4
 
1.2%
Other values (4) 8
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2390
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 263
11.0%
259
10.8%
l 255
10.7%
e 247
10.3%
S 241
10.1%
p 240
10.0%
m 240
10.0%
O 240
10.0%
Y 240
10.0%
o 19
 
0.8%
Other values (34) 146
6.1%

eventDate
Text

Missing 

Distinct100743
Distinct (%)2.5%
Missing499507
Missing (%)11.1%
Memory size34.5 MiB
2025-01-14T11:45:24.779886image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length10
Mean length10.22911024
Min length4

Characters and Unicode

Total characters41081682
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26184 ?
Unique (%)0.7%

Sample

1st row1981-04-30
2nd row1954-08-07
3rd row1947-04-03
4th row1966-04-01
5th row1971-03-23
ValueCountFrequency (%)
or 7511
 
0.2%
1838/1842 6999
 
0.2%
1891 4648
 
0.1%
1760/1808 3657
 
0.1%
1889 3487
 
0.1%
1875 3339
 
0.1%
1853/1856 3324
 
0.1%
1890 3156
 
0.1%
1923 3139
 
0.1%
1887 3048
 
0.1%
Other values (96839) 3988868
99.0%
2025-01-14T11:45:25.056780image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7801445
19.0%
- 7726696
18.8%
0 6238271
15.2%
9 5176217
12.6%
2 3077613
 
7.5%
8 2443585
 
5.9%
7 1744336
 
4.2%
6 1741318
 
4.2%
3 1670243
 
4.1%
5 1552877
 
3.8%
Other values (6) 1909081
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32969564
80.3%
Dash Punctuation 7726696
 
18.8%
Other Punctuation 355378
 
0.9%
Space Separator 15022
 
< 0.1%
Lowercase Letter 15022
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7801445
23.7%
0 6238271
18.9%
9 5176217
15.7%
2 3077613
 
9.3%
8 2443585
 
7.4%
7 1744336
 
5.3%
6 1741318
 
5.3%
3 1670243
 
5.1%
5 1552877
 
4.7%
4 1523659
 
4.6%
Other Punctuation
ValueCountFrequency (%)
/ 347825
97.9%
, 7553
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
o 7511
50.0%
r 7511
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 7726696
100.0%
Space Separator
ValueCountFrequency (%)
15022
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 41066660
> 99.9%
Latin 15022
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7801445
19.0%
- 7726696
18.8%
0 6238271
15.2%
9 5176217
12.6%
2 3077613
 
7.5%
8 2443585
 
6.0%
7 1744336
 
4.2%
6 1741318
 
4.2%
3 1670243
 
4.1%
5 1552877
 
3.8%
Other values (4) 1894059
 
4.6%
Latin
ValueCountFrequency (%)
o 7511
50.0%
r 7511
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41081682
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7801445
19.0%
- 7726696
18.8%
0 6238271
15.2%
9 5176217
12.6%
2 3077613
 
7.5%
8 2443585
 
5.9%
7 1744336
 
4.2%
6 1741318
 
4.2%
3 1670243
 
4.1%
5 1552877
 
3.8%
Other values (6) 1909081
 
4.6%

startDayOfYear
Text

Missing 

Distinct366
Distinct (%)< 0.1%
Missing707937
Missing (%)15.7%
Memory size34.5 MiB
2025-01-14T11:45:25.266624image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.786185921
Min length1

Characters and Unicode

Total characters10609027
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row120
2nd row219
3rd row93
4th row91
5th row82
ValueCountFrequency (%)
212 65252
 
1.7%
243 53926
 
1.4%
181 53248
 
1.4%
151 48909
 
1.3%
120 37888
 
1.0%
213 35186
 
0.9%
273 34755
 
0.9%
90 31604
 
0.8%
304 30708
 
0.8%
244 28680
 
0.8%
Other values (356) 3387568
89.0%
2025-01-14T11:45:25.543384image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2141855
20.2%
2 2135625
20.1%
3 1271069
12.0%
4 814683
 
7.7%
5 784204
 
7.4%
0 747144
 
7.0%
9 692015
 
6.5%
6 686000
 
6.5%
8 680008
 
6.4%
7 656424
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10609027
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2141855
20.2%
2 2135625
20.1%
3 1271069
12.0%
4 814683
 
7.7%
5 784204
 
7.4%
0 747144
 
7.0%
9 692015
 
6.5%
6 686000
 
6.5%
8 680008
 
6.4%
7 656424
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 10609027
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2141855
20.2%
2 2135625
20.1%
3 1271069
12.0%
4 814683
 
7.7%
5 784204
 
7.4%
0 747144
 
7.0%
9 692015
 
6.5%
6 686000
 
6.5%
8 680008
 
6.4%
7 656424
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10609027
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2141855
20.2%
2 2135625
20.1%
3 1271069
12.0%
4 814683
 
7.7%
5 784204
 
7.4%
0 747144
 
7.0%
9 692015
 
6.5%
6 686000
 
6.5%
8 680008
 
6.4%
7 656424
 
6.2%

endDayOfYear
Text

Missing 

Distinct366
Distinct (%)< 0.1%
Missing706297
Missing (%)15.6%
Memory size34.5 MiB
2025-01-14T11:45:25.761464image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.787330116
Min length1

Characters and Unicode

Total characters10617955
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row120
2nd row219
3rd row93
4th row91
5th row82
ValueCountFrequency (%)
212 66123
 
1.7%
243 57269
 
1.5%
181 53207
 
1.4%
151 44291
 
1.2%
120 37736
 
1.0%
273 36145
 
0.9%
90 33356
 
0.9%
304 33021
 
0.9%
213 32570
 
0.9%
244 30634
 
0.8%
Other values (356) 3385012
88.9%
2025-01-14T11:45:26.047333image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2140880
20.2%
1 2116002
19.9%
3 1288304
12.1%
4 826923
 
7.8%
5 780021
 
7.3%
0 749805
 
7.1%
9 689036
 
6.5%
6 683421
 
6.4%
8 681866
 
6.4%
7 661697
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10617955
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2140880
20.2%
1 2116002
19.9%
3 1288304
12.1%
4 826923
 
7.8%
5 780021
 
7.3%
0 749805
 
7.1%
9 689036
 
6.5%
6 683421
 
6.4%
8 681866
 
6.4%
7 661697
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 10617955
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2140880
20.2%
1 2116002
19.9%
3 1288304
12.1%
4 826923
 
7.8%
5 780021
 
7.3%
0 749805
 
7.1%
9 689036
 
6.5%
6 683421
 
6.4%
8 681866
 
6.4%
7 661697
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10617955
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2140880
20.2%
1 2116002
19.9%
3 1288304
12.1%
4 826923
 
7.8%
5 780021
 
7.3%
0 749805
 
7.1%
9 689036
 
6.5%
6 683421
 
6.4%
8 681866
 
6.4%
7 661697
 
6.2%

year
Text

Missing 

Distinct275
Distinct (%)< 0.1%
Missing499507
Missing (%)11.1%
Memory size34.5 MiB
2025-01-14T11:45:26.270965image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters16064616
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)< 0.1%

Sample

1st row1981
2nd row1954
3rd row1947
4th row1966
5th row1971
ValueCountFrequency (%)
1966 52747
 
1.3%
1964 51506
 
1.3%
1939 48539
 
1.2%
1949 46743
 
1.2%
1929 45873
 
1.1%
1938 44996
 
1.1%
1965 44897
 
1.1%
1922 42897
 
1.1%
1962 42322
 
1.1%
1968 41351
 
1.0%
Other values (265) 3554283
88.5%
2025-01-14T11:45:26.546590image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4564194
28.4%
9 4113450
25.6%
8 1419370
 
8.8%
0 1047460
 
6.5%
2 964799
 
6.0%
6 886880
 
5.5%
4 787306
 
4.9%
3 776965
 
4.8%
7 755520
 
4.7%
5 748672
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16064616
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4564194
28.4%
9 4113450
25.6%
8 1419370
 
8.8%
0 1047460
 
6.5%
2 964799
 
6.0%
6 886880
 
5.5%
4 787306
 
4.9%
3 776965
 
4.8%
7 755520
 
4.7%
5 748672
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
Common 16064616
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4564194
28.4%
9 4113450
25.6%
8 1419370
 
8.8%
0 1047460
 
6.5%
2 964799
 
6.0%
6 886880
 
5.5%
4 787306
 
4.9%
3 776965
 
4.8%
7 755520
 
4.7%
5 748672
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16064616
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4564194
28.4%
9 4113450
25.6%
8 1419370
 
8.8%
0 1047460
 
6.5%
2 964799
 
6.0%
6 886880
 
5.5%
4 787306
 
4.9%
3 776965
 
4.8%
7 755520
 
4.7%
5 748672
 
4.7%

month
Text

Missing 

Distinct12
Distinct (%)< 0.1%
Missing700051
Missing (%)15.5%
Memory size34.5 MiB
2025-01-14T11:45:26.614629image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.171101868
Min length1

Characters and Unicode

Total characters4468468
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row8
3rd row4
4th row4
5th row3
ValueCountFrequency (%)
7 547270
14.3%
8 491637
12.9%
6 411350
10.8%
5 354199
9.3%
9 340693
8.9%
4 293710
7.7%
3 268012
7.0%
10 260725
6.8%
2 235530
6.2%
1 220351
5.8%
Other values (2) 392133
10.3%
2025-01-14T11:45:26.726290image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1080650
24.2%
7 547270
12.2%
8 491637
11.0%
2 420222
 
9.4%
6 411350
 
9.2%
5 354199
 
7.9%
9 340693
 
7.6%
4 293710
 
6.6%
3 268012
 
6.0%
0 260725
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4468468
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1080650
24.2%
7 547270
12.2%
8 491637
11.0%
2 420222
 
9.4%
6 411350
 
9.2%
5 354199
 
7.9%
9 340693
 
7.6%
4 293710
 
6.6%
3 268012
 
6.0%
0 260725
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
Common 4468468
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1080650
24.2%
7 547270
12.2%
8 491637
11.0%
2 420222
 
9.4%
6 411350
 
9.2%
5 354199
 
7.9%
9 340693
 
7.6%
4 293710
 
6.6%
3 268012
 
6.0%
0 260725
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4468468
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1080650
24.2%
7 547270
12.2%
8 491637
11.0%
2 420222
 
9.4%
6 411350
 
9.2%
5 354199
 
7.9%
9 340693
 
7.6%
4 293710
 
6.6%
3 268012
 
6.0%
0 260725
 
5.8%

day
Text

Missing 

Distinct31
Distinct (%)< 0.1%
Missing1180026
Missing (%)26.1%
Memory size34.5 MiB
2025-01-14T11:45:26.798942image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.709506586
Min length1

Characters and Unicode

Total characters5702290
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30
2nd row7
3rd row3
4th row1
5th row23
ValueCountFrequency (%)
20 124820
 
3.7%
15 121526
 
3.6%
10 116402
 
3.5%
1 116290
 
3.5%
18 114533
 
3.4%
25 112462
 
3.4%
19 112076
 
3.4%
17 111731
 
3.3%
12 111029
 
3.3%
8 109940
 
3.3%
Other values (21) 2184826
65.5%
2025-01-14T11:45:26.926666image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1506435
26.4%
2 1419764
24.9%
3 471332
 
8.3%
5 342700
 
6.0%
0 340158
 
6.0%
8 333415
 
5.8%
7 328337
 
5.8%
6 325244
 
5.7%
4 321679
 
5.6%
9 313226
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5702290
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1506435
26.4%
2 1419764
24.9%
3 471332
 
8.3%
5 342700
 
6.0%
0 340158
 
6.0%
8 333415
 
5.8%
7 328337
 
5.8%
6 325244
 
5.7%
4 321679
 
5.6%
9 313226
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
Common 5702290
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1506435
26.4%
2 1419764
24.9%
3 471332
 
8.3%
5 342700
 
6.0%
0 340158
 
6.0%
8 333415
 
5.8%
7 328337
 
5.8%
6 325244
 
5.7%
4 321679
 
5.6%
9 313226
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5702290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1506435
26.4%
2 1419764
24.9%
3 471332
 
8.3%
5 342700
 
6.0%
0 340158
 
6.0%
8 333415
 
5.8%
7 328337
 
5.8%
6 325244
 
5.7%
4 321679
 
5.6%
9 313226
 
5.5%

verbatimEventDate
Text

Missing 

Distinct144603
Distinct (%)9.5%
Missing2995056
Missing (%)66.3%
Memory size34.5 MiB
2025-01-14T11:45:27.122036image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length44726
Median length11
Mean length13.4161199
Min length1

Characters and Unicode

Total characters20400619
Distinct characters110
Distinct categories16 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47164 ?
Unique (%)3.1%

Sample

1st row30 Apr 1981
2nd row16 Dec 1953
3rd row-- --- ----
4th row01 Feb 1974
5th rowTranscribed d/m/y: 28/4/76
ValueCountFrequency (%)
569685
 
12.1%
transcribed 163800
 
3.5%
d/m/y 163799
 
3.5%
jul 133516
 
2.8%
aug 127314
 
2.7%
may 100704
 
2.1%
sep 100407
 
2.1%
jun 99914
 
2.1%
mar 89911
 
1.9%
to 89366
 
1.9%
Other values (50980) 3069137
65.2%
2025-01-14T11:45:27.399778image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3184972
15.6%
1 2057978
 
10.1%
- 1706716
 
8.4%
9 1491498
 
7.3%
2 903531
 
4.4%
0 760159
 
3.7%
/ 668632
 
3.3%
8 665330
 
3.3%
r 587998
 
2.9%
e 493324
 
2.4%
Other values (100) 7880481
38.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8113118
39.8%
Lowercase Letter 5099499
25.0%
Space Separator 3184972
 
15.6%
Dash Punctuation 1706716
 
8.4%
Uppercase Letter 1427985
 
7.0%
Other Punctuation 856153
 
4.2%
Control 11040
 
0.1%
Open Punctuation 519
 
< 0.1%
Close Punctuation 515
 
< 0.1%
Math Symbol 76
 
< 0.1%
Other values (6) 26
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 587998
11.5%
e 493324
 
9.7%
a 480500
 
9.4%
u 422327
 
8.3%
n 369730
 
7.3%
d 335298
 
6.6%
c 329419
 
6.5%
y 293646
 
5.8%
b 281590
 
5.5%
p 221434
 
4.3%
Other values (31) 1284233
25.2%
Uppercase Letter
ValueCountFrequency (%)
J 346402
24.3%
A 244422
17.1%
M 212179
14.9%
T 165091
11.6%
S 118257
 
8.3%
F 97247
 
6.8%
O 92390
 
6.5%
N 75920
 
5.3%
D 66935
 
4.7%
I 3031
 
0.2%
Other values (20) 6111
 
0.4%
Other Punctuation
ValueCountFrequency (%)
/ 668632
78.1%
: 164474
 
19.2%
, 11572
 
1.4%
. 9358
 
1.1%
' 713
 
0.1%
? 654
 
0.1%
! 466
 
0.1%
; 146
 
< 0.1%
& 67
 
< 0.1%
* 53
 
< 0.1%
Other values (2) 18
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 2057978
25.4%
9 1491498
18.4%
2 903531
11.1%
0 760159
 
9.4%
8 665330
 
8.2%
6 485773
 
6.0%
3 469301
 
5.8%
4 428035
 
5.3%
7 426717
 
5.3%
5 424796
 
5.2%
Math Symbol
ValueCountFrequency (%)
= 69
90.8%
+ 4
 
5.3%
± 3
 
3.9%
Control
ValueCountFrequency (%)
10982
99.5%
58
 
0.5%
Open Punctuation
ValueCountFrequency (%)
[ 269
51.8%
( 250
48.2%
Close Punctuation
ValueCountFrequency (%)
] 265
51.5%
) 250
48.5%
Space Separator
ValueCountFrequency (%)
3184972
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1706716
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 18
100.0%
Other Number
ValueCountFrequency (%)
½ 3
100.0%
Other Symbol
ValueCountFrequency (%)
° 2
100.0%
Other Letter
ValueCountFrequency (%)
º 1
100.0%
Modifier Letter
ValueCountFrequency (%)
ᵉ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
” 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13873133
68.0%
Latin 6527486
32.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 587998
 
9.0%
e 493324
 
7.6%
a 480500
 
7.4%
u 422327
 
6.5%
n 369730
 
5.7%
J 346402
 
5.3%
d 335298
 
5.1%
c 329419
 
5.0%
y 293646
 
4.5%
b 281590
 
4.3%
Other values (63) 2587252
39.6%
Common
ValueCountFrequency (%)
3184972
23.0%
1 2057978
14.8%
- 1706716
12.3%
9 1491498
10.8%
2 903531
 
6.5%
0 760159
 
5.5%
/ 668632
 
4.8%
8 665330
 
4.8%
6 485773
 
3.5%
3 469301
 
3.4%
Other values (27) 1479243
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20400500
> 99.9%
None 117
 
< 0.1%
Phonetic Ext 1
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3184972
15.6%
1 2057978
 
10.1%
- 1706716
 
8.4%
9 1491498
 
7.3%
2 903531
 
4.4%
0 760159
 
3.7%
/ 668632
 
3.3%
8 665330
 
3.3%
r 587998
 
2.9%
e 493324
 
2.4%
Other values (75) 7880362
38.6%
None
ValueCountFrequency (%)
é 41
35.0%
û 16
 
13.7%
Æ 8
 
6.8%
ó 8
 
6.8%
ü 7
 
6.0%
á 5
 
4.3%
í 5
 
4.3%
ô 4
 
3.4%
½ 3
 
2.6%
± 3
 
2.6%
Other values (13) 17
14.5%
Phonetic Ext
ValueCountFrequency (%)
ᵉ 1
100.0%
Punctuation
ValueCountFrequency (%)
” 1
100.0%

habitat
Text

Missing 

Distinct179316
Distinct (%)35.4%
Missing4009333
Missing (%)88.8%
Memory size34.5 MiB
2025-01-14T11:45:27.610562image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length98062
Median length506
Mean length33.74884265
Min length1

Characters and Unicode

Total characters17087984
Distinct characters145
Distinct categories18 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136896 ?
Unique (%)27.0%

Sample

1st rowErect.
2nd rowPlanted
3rd rowHillsides covered with broad-leaved forest, understory with Arthrostylidium, Rubus, and numerous ferns, epiphytes and Usnea.
4th rowOpen to closed forest with Pinus contorta, Populus tremuloides, Purshia tridentata, and Ribes cereum.
5th rowDeep secondary forest; clay soil
ValueCountFrequency (%)
forest 131247
 
5.0%
on 90052
 
3.4%
and 73888
 
2.8%
in 67428
 
2.6%
with 54107
 
2.1%
of 49767
 
1.9%
along 29262
 
1.1%
de 27744
 
1.1%
soil 24644
 
0.9%
slopes 22332
 
0.9%
Other values (44622) 2044337
78.2%
2025-01-14T11:45:27.895749image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2101244
 
12.3%
e 1541379
 
9.0%
a 1348535
 
7.9%
o 1227275
 
7.2%
r 1069847
 
6.3%
s 1066411
 
6.2%
n 1051888
 
6.2%
i 901575
 
5.3%
t 853198
 
5.0%
l 666293
 
3.9%
Other values (135) 5260339
30.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13594397
79.6%
Space Separator 2101244
 
12.3%
Uppercase Letter 746465
 
4.4%
Other Punctuation 472867
 
2.8%
Decimal Number 67702
 
0.4%
Dash Punctuation 40071
 
0.2%
Control 39873
 
0.2%
Close Punctuation 10898
 
0.1%
Open Punctuation 10825
 
0.1%
Math Symbol 3419
 
< 0.1%
Other values (8) 223
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1541379
11.3%
a 1348535
9.9%
o 1227275
 
9.0%
r 1069847
 
7.9%
s 1066411
 
7.8%
n 1051888
 
7.7%
i 901575
 
6.6%
t 853198
 
6.3%
l 666293
 
4.9%
d 655799
 
4.8%
Other values (47) 3212197
23.6%
Uppercase Letter
ValueCountFrequency (%)
S 91327
12.2%
M 68847
 
9.2%
C 52021
 
7.0%
P 49180
 
6.6%
O 46573
 
6.2%
A 46219
 
6.2%
R 44856
 
6.0%
D 41895
 
5.6%
B 40944
 
5.5%
F 39683
 
5.3%
Other values (21) 224920
30.1%
Other Punctuation
ValueCountFrequency (%)
, 205238
43.4%
. 204309
43.2%
; 28753
 
6.1%
& 10542
 
2.2%
/ 7989
 
1.7%
: 7982
 
1.7%
" 3600
 
0.8%
' 2231
 
0.5%
? 964
 
0.2%
% 677
 
0.1%
Other values (6) 582
 
0.1%
Decimal Number
ValueCountFrequency (%)
0 16184
23.9%
1 9224
13.6%
3 8235
12.2%
2 7849
11.6%
5 7153
10.6%
4 5839
 
8.6%
6 4326
 
6.4%
8 3600
 
5.3%
9 2857
 
4.2%
7 2435
 
3.6%
Math Symbol
ValueCountFrequency (%)
~ 1916
56.0%
| 579
 
16.9%
+ 396
 
11.6%
= 268
 
7.8%
± 193
 
5.6%
> 35
 
1.0%
< 30
 
0.9%
≤ 1
 
< 0.1%
× 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 40030
99.9%
– 27
 
0.1%
— 14
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 10326
94.8%
] 356
 
3.3%
} 216
 
2.0%
Open Punctuation
ValueCountFrequency (%)
( 10271
94.9%
[ 337
 
3.1%
{ 217
 
2.0%
Control
ValueCountFrequency (%)
39663
99.5%
210
 
0.5%
Other Symbol
ValueCountFrequency (%)
° 116
99.1%
¦ 1
 
0.9%
Modifier Symbol
ValueCountFrequency (%)
^ 2
66.7%
´ 1
33.3%
Space Separator
ValueCountFrequency (%)
2101244
100.0%
Final Punctuation
ValueCountFrequency (%)
” 31
100.0%
Other Letter
ValueCountFrequency (%)
º 25
100.0%
Initial Punctuation
ValueCountFrequency (%)
“ 22
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 20
100.0%
Other Number
ValueCountFrequency (%)
² 3
100.0%
Currency Symbol
ValueCountFrequency (%)
£ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14340887
83.9%
Common 2747097
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1541379
 
10.7%
a 1348535
 
9.4%
o 1227275
 
8.6%
r 1069847
 
7.5%
s 1066411
 
7.4%
n 1051888
 
7.3%
i 901575
 
6.3%
t 853198
 
5.9%
l 666293
 
4.6%
d 655799
 
4.6%
Other values (79) 3958687
27.6%
Common
ValueCountFrequency (%)
2101244
76.5%
, 205238
 
7.5%
. 204309
 
7.4%
- 40030
 
1.5%
39663
 
1.4%
; 28753
 
1.0%
0 16184
 
0.6%
& 10542
 
0.4%
) 10326
 
0.4%
( 10271
 
0.4%
Other values (46) 80537
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17056686
99.8%
None 31039
 
0.2%
Punctuation 258
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2101244
12.3%
e 1541379
 
9.0%
a 1348535
 
7.9%
o 1227275
 
7.2%
r 1069847
 
6.3%
s 1066411
 
6.3%
n 1051888
 
6.2%
i 901575
 
5.3%
t 853198
 
5.0%
l 666293
 
3.9%
Other values (85) 5229041
30.7%
None
ValueCountFrequency (%)
ú 4630
14.9%
é 4538
14.6%
ê 4416
14.2%
ó 4352
14.0%
í 3568
11.5%
á 3212
10.3%
ñ 2452
7.9%
è 1544
 
5.0%
à 606
 
2.0%
ã 253
 
0.8%
Other values (34) 1468
 
4.7%
Punctuation
ValueCountFrequency (%)
… 164
63.6%
” 31
 
12.0%
– 27
 
10.5%
“ 22
 
8.5%
— 14
 
5.4%
Math Operators
ValueCountFrequency (%)
≤ 1
100.0%

samplingProtocol
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing4515660
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:27.953958image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row400.0
ValueCountFrequency (%)
400.0 1
100.0%
2025-01-14T11:45:28.052830image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3
60.0%
4 1
 
20.0%
. 1
 
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
80.0%
Other Punctuation 1
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3
75.0%
4 1
 
25.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3
60.0%
4 1
 
20.0%
. 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3
60.0%
4 1
 
20.0%
. 1
 
20.0%

sampleSizeValue
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing4515659
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:28.099142image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5.5
Mean length5.5
Min length5

Characters and Unicode

Total characters11
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row500.0
2nd row1000.0
ValueCountFrequency (%)
500.0 1
50.0%
1000.0 1
50.0%
2025-01-14T11:45:28.202973image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7
63.6%
. 2
 
18.2%
5 1
 
9.1%
1 1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
81.8%
Other Punctuation 2
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7
77.8%
5 1
 
11.1%
1 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7
63.6%
. 2
 
18.2%
5 1
 
9.1%
1 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7
63.6%
. 2
 
18.2%
5 1
 
9.1%
1 1
 
9.1%

locationID
Text

Missing 

Distinct1108
Distinct (%)2.7%
Missing4473993
Missing (%)99.1%
Memory size34.5 MiB
2025-01-14T11:45:28.394902image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length37
Median length5
Mean length5.995968129
Min length1

Characters and Unicode

Total characters249840
Distinct characters72
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique362 ?
Unique (%)0.9%

Sample

1st row66-10
2nd row69-11
3rd row64-51
4th row66-14
5th row64-34
ValueCountFrequency (%)
station 4948
 
10.3%
ms04 1735
 
3.6%
66-24 1381
 
2.9%
61 946
 
2.0%
64-48 628
 
1.3%
64-47 588
 
1.2%
69-14 562
 
1.2%
66-39 462
 
1.0%
66-28 442
 
0.9%
66-17 426
 
0.9%
Other values (1007) 36062
74.8%
2025-01-14T11:45:28.677082image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 43817
17.5%
- 36322
14.5%
4 21703
 
8.7%
2 20165
 
8.1%
1 18260
 
7.3%
0 15408
 
6.2%
3 11182
 
4.5%
7 10459
 
4.2%
t 10132
 
4.1%
8 7703
 
3.1%
Other values (62) 54689
21.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160264
64.1%
Dash Punctuation 36322
 
14.5%
Lowercase Letter 31510
 
12.6%
Uppercase Letter 14701
 
5.9%
Space Separator 6512
 
2.6%
Connector Punctuation 289
 
0.1%
Close Punctuation 104
 
< 0.1%
Open Punctuation 104
 
< 0.1%
Other Punctuation 33
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 7597
51.7%
M 1888
 
12.8%
A 1171
 
8.0%
I 758
 
5.2%
K 734
 
5.0%
N 501
 
3.4%
T 368
 
2.5%
H 276
 
1.9%
O 207
 
1.4%
B 205
 
1.4%
Other values (16) 996
 
6.8%
Lowercase Letter
ValueCountFrequency (%)
t 10132
32.2%
o 5161
16.4%
n 5158
16.4%
i 5089
16.2%
a 5076
16.1%
e 241
 
0.8%
r 113
 
0.4%
l 104
 
0.3%
d 82
 
0.3%
s 80
 
0.3%
Other values (12) 274
 
0.9%
Decimal Number
ValueCountFrequency (%)
6 43817
27.3%
4 21703
13.5%
2 20165
12.6%
1 18260
11.4%
0 15408
 
9.6%
3 11182
 
7.0%
7 10459
 
6.5%
8 7703
 
4.8%
9 5892
 
3.7%
5 5675
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 14
42.4%
/ 9
27.3%
& 4
 
12.1%
. 4
 
12.1%
? 1
 
3.0%
\ 1
 
3.0%
Close Punctuation
ValueCountFrequency (%)
) 102
98.1%
] 2
 
1.9%
Open Punctuation
ValueCountFrequency (%)
( 102
98.1%
[ 2
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 36322
100.0%
Space Separator
ValueCountFrequency (%)
6512
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 289
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 203629
81.5%
Latin 46211
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 10132
21.9%
S 7597
16.4%
o 5161
11.2%
n 5158
11.2%
i 5089
11.0%
a 5076
11.0%
M 1888
 
4.1%
A 1171
 
2.5%
I 758
 
1.6%
K 734
 
1.6%
Other values (38) 3447
 
7.5%
Common
ValueCountFrequency (%)
6 43817
21.5%
- 36322
17.8%
4 21703
10.7%
2 20165
9.9%
1 18260
9.0%
0 15408
 
7.6%
3 11182
 
5.5%
7 10459
 
5.1%
8 7703
 
3.8%
6512
 
3.2%
Other values (14) 12098
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 249840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 43817
17.5%
- 36322
14.5%
4 21703
 
8.7%
2 20165
 
8.1%
1 18260
 
7.3%
0 15408
 
6.2%
3 11182
 
4.5%
7 10459
 
4.2%
t 10132
 
4.1%
8 7703
 
3.1%
Other values (62) 54689
21.9%

higherGeography
Text

Distinct29227
Distinct (%)0.7%
Missing38628
Missing (%)0.9%
Memory size34.5 MiB
2025-01-14T11:45:28.892467image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length136
Median length118
Mean length40.94742545
Min length4

Characters and Unicode

Total characters183322975
Distinct characters163
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9052 ?
Unique (%)0.2%

Sample

1st rowNorth America, United States, Florida
2nd rowSouth America - Neotropics, Peru, Piura
3rd rowSouth America, Argentina, Formosa
4th rowSouth America - Neotropics, Venezuela, Carabobo
5th rowAfrica, South Africa
ValueCountFrequency (%)
america 3037857
 
12.5%
north 1751165
 
7.2%
1668629
 
6.8%
neotropics 1604866
 
6.6%
united 1351633
 
5.5%
states 1342475
 
5.5%
south 1161951
 
4.8%
mexico 330187
 
1.4%
asia-tropical 303950
 
1.2%
brazil 299921
 
1.2%
Other values (15123) 11516200
47.3%
2025-01-14T11:45:29.185601image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19891801
 
10.9%
a 16902477
 
9.2%
i 13659346
 
7.5%
e 13427066
 
7.3%
r 11621631
 
6.3%
t 11453417
 
6.2%
o 11169195
 
6.1%
, 9361908
 
5.1%
n 7219729
 
3.9%
c 7113809
 
3.9%
Other values (153) 61502596
33.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 128373886
70.0%
Uppercase Letter 23155087
 
12.6%
Space Separator 19891801
 
10.9%
Other Punctuation 9561674
 
5.2%
Dash Punctuation 2254209
 
1.2%
Close Punctuation 42797
 
< 0.1%
Open Punctuation 42786
 
< 0.1%
Modifier Letter 501
 
< 0.1%
Modifier Symbol 124
 
< 0.1%
Decimal Number 105
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 16902477
13.2%
i 13659346
10.6%
e 13427066
10.5%
r 11621631
9.1%
t 11453417
8.9%
o 11169195
8.7%
n 7219729
 
5.6%
c 7113809
 
5.5%
s 6918837
 
5.4%
m 4346665
 
3.4%
Other values (72) 24541714
19.1%
Uppercase Letter
ValueCountFrequency (%)
A 4555726
19.7%
N 3785910
16.4%
S 3179005
13.7%
C 1820326
 
7.9%
U 1509030
 
6.5%
M 989360
 
4.3%
P 911762
 
3.9%
I 836682
 
3.6%
T 836579
 
3.6%
B 695897
 
3.0%
Other values (38) 4034810
17.4%
Other Punctuation
ValueCountFrequency (%)
, 9361908
97.9%
. 135896
 
1.4%
' 40694
 
0.4%
/ 21497
 
0.2%
? 1508
 
< 0.1%
& 139
 
< 0.1%
" 14
 
< 0.1%
; 9
 
< 0.1%
\ 4
 
< 0.1%
: 3
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 46
43.8%
2 46
43.8%
3 5
 
4.8%
6 3
 
2.9%
4 2
 
1.9%
7 2
 
1.9%
9 1
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 26456
61.8%
] 16340
38.2%
} 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 2254206
> 99.9%
– 3
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 26444
61.8%
[ 16342
38.2%
Modifier Letter
ValueCountFrequency (%)
ʻ 442
88.2%
ʼ 59
 
11.8%
Modifier Symbol
ValueCountFrequency (%)
´ 123
99.2%
¸ 1
 
0.8%
Math Symbol
ValueCountFrequency (%)
= 1
50.0%
+ 1
50.0%
Space Separator
ValueCountFrequency (%)
19891801
100.0%
Nonspacing Mark
ValueCountFrequency (%)
́ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 151528973
82.7%
Common 31793999
 
17.3%
Inherited 3
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 16902477
 
11.2%
i 13659346
 
9.0%
e 13427066
 
8.9%
r 11621631
 
7.7%
t 11453417
 
7.6%
o 11169195
 
7.4%
n 7219729
 
4.8%
c 7113809
 
4.7%
s 6918837
 
4.6%
A 4555726
 
3.0%
Other values (120) 47487740
31.3%
Common
ValueCountFrequency (%)
19891801
62.6%
, 9361908
29.4%
- 2254206
 
7.1%
. 135896
 
0.4%
' 40694
 
0.1%
) 26456
 
0.1%
( 26444
 
0.1%
/ 21497
 
0.1%
[ 16342
 
0.1%
] 16340
 
0.1%
Other values (22) 2415
 
< 0.1%
Inherited
ValueCountFrequency (%)
́ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 182844363
99.7%
None 478071
 
0.3%
Modifier Letters 501
 
< 0.1%
Latin Ext Additional 34
 
< 0.1%
Punctuation 3
 
< 0.1%
Diacriticals 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19891801
 
10.9%
a 16902477
 
9.2%
i 13659346
 
7.5%
e 13427066
 
7.3%
r 11621631
 
6.4%
t 11453417
 
6.3%
o 11169195
 
6.1%
, 9361908
 
5.1%
n 7219729
 
3.9%
c 7113809
 
3.9%
Other values (68) 61023984
33.4%
None
ValueCountFrequency (%)
á 158373
33.1%
í 91518
19.1%
é 80944
16.9%
ó 57377
 
12.0%
ã 28755
 
6.0%
ô 13770
 
2.9%
ç 8254
 
1.7%
ñ 7290
 
1.5%
Î 6683
 
1.4%
ü 5257
 
1.1%
Other values (59) 19850
 
4.2%
Modifier Letters
ValueCountFrequency (%)
ʻ 442
88.2%
ʼ 59
 
11.8%
Latin Ext Additional
ValueCountFrequency (%)
ḍ 10
29.4%
ṭ 8
23.5%
ồ 3
 
8.8%
ị 2
 
5.9%
ế 2
 
5.9%
ả 2
 
5.9%
ộ 2
 
5.9%
ẵ 1
 
2.9%
ḑ 1
 
2.9%
ừ 1
 
2.9%
Other values (2) 2
 
5.9%
Punctuation
ValueCountFrequency (%)
– 3
100.0%
Diacriticals
ValueCountFrequency (%)
́ 3
100.0%

continent
Text

Missing 

Distinct72
Distinct (%)< 0.1%
Missing66158
Missing (%)1.5%
Memory size34.5 MiB
2025-01-14T11:45:29.264395image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length57
Median length50
Mean length17.22849923
Min length4

Characters and Unicode

Total characters76658259
Distinct characters40
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)< 0.1%

Sample

1st rowNorth America
2nd rowSouth America - Neotropics
3rd rowSouth America
4th rowSouth America - Neotropics
5th rowAfrica
ValueCountFrequency (%)
america 3037856
27.2%
north 1705271
15.3%
1605982
14.4%
neotropics 1604866
14.4%
south 1078261
 
9.7%
asia-tropical 303950
 
2.7%
central 269843
 
2.4%
west 265195
 
2.4%
indies 265195
 
2.4%
europe 230947
 
2.1%
Other values (19) 796938
 
7.1%
2025-01-14T11:45:29.391948image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 7607800
 
9.9%
6714801
 
8.8%
o 6532692
 
8.5%
e 6336991
 
8.3%
i 6293342
 
8.2%
c 5457494
 
7.1%
t 5250425
 
6.8%
a 5072337
 
6.6%
A 3811578
 
5.0%
N 3310135
 
4.3%
Other values (30) 20270664
26.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 57722814
75.3%
Uppercase Letter 10079210
 
13.1%
Space Separator 6714801
 
8.8%
Dash Punctuation 2124592
 
2.8%
Other Punctuation 16840
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 7607800
13.2%
o 6532692
11.3%
e 6336991
11.0%
i 6293342
10.9%
c 5457494
9.5%
t 5250425
9.1%
a 5072337
8.8%
m 3253669
5.6%
s 3104060
5.4%
h 2783537
 
4.8%
Other values (10) 6030467
10.4%
Uppercase Letter
ValueCountFrequency (%)
A 3811578
37.8%
N 3310135
32.8%
S 1078416
 
10.7%
T 519589
 
5.2%
I 418416
 
4.2%
C 269978
 
2.7%
W 265195
 
2.6%
E 230947
 
2.3%
P 154152
 
1.5%
O 15874
 
0.2%
Other values (3) 4930
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
, 15724
93.4%
/ 1115
 
6.6%
? 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
6714801
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2124592
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 67802024
88.4%
Common 8856235
 
11.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 7607800
11.2%
o 6532692
9.6%
e 6336991
9.3%
i 6293342
9.3%
c 5457494
 
8.0%
t 5250425
 
7.7%
a 5072337
 
7.5%
A 3811578
 
5.6%
N 3310135
 
4.9%
m 3253669
 
4.8%
Other values (23) 14875561
21.9%
Common
ValueCountFrequency (%)
6714801
75.8%
- 2124592
 
24.0%
, 15724
 
0.2%
/ 1115
 
< 0.1%
( 1
 
< 0.1%
? 1
 
< 0.1%
) 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76658259
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 7607800
 
9.9%
6714801
 
8.8%
o 6532692
 
8.5%
e 6336991
 
8.3%
i 6293342
 
8.2%
c 5457494
 
7.1%
t 5250425
 
6.8%
a 5072337
 
6.6%
A 3811578
 
5.0%
N 3310135
 
4.3%
Other values (30) 20270664
26.4%

waterBody
Text

Missing 

Distinct146
Distinct (%)0.7%
Missing4496088
Missing (%)99.6%
Memory size34.5 MiB
2025-01-14T11:45:29.480648image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length62
Median length61
Mean length26.33765902
Min length4

Characters and Unicode

Total characters515507
Distinct characters58
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)0.3%

Sample

1st rowNorth Atlantic Ocean, Bay of Fundy
2nd rowNorth Atlantic Ocean, Caribbean Sea
3rd rowNorth Atlantic Ocean, Gulf of Maine, Englishman Bay/Mack Cove
4th rowNorth Atlantic Ocean, Caribbean Sea
5th rowNorth Pacific Ocean
ValueCountFrequency (%)
ocean 15739
19.7%
north 15146
19.0%
atlantic 14293
17.9%
sea 7188
9.0%
caribbean 6009
 
7.5%
of 3765
 
4.7%
gulf 3584
 
4.5%
maine 2788
 
3.5%
bay 2525
 
3.2%
pacific 1232
 
1.5%
Other values (153) 7583
9.5%
2025-01-14T11:45:29.646029image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
60279
11.7%
a 59587
11.6%
t 46425
 
9.0%
n 42137
 
8.2%
e 36547
 
7.1%
c 34220
 
6.6%
i 27759
 
5.4%
r 23435
 
4.5%
o 23395
 
4.5%
l 19298
 
3.7%
Other values (48) 142425
27.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 367426
71.3%
Uppercase Letter 76511
 
14.8%
Space Separator 60279
 
11.7%
Other Punctuation 10843
 
2.1%
Modifier Letter 442
 
0.1%
Dash Punctuation 4
 
< 0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 59587
16.2%
t 46425
12.6%
n 42137
11.5%
e 36547
9.9%
c 34220
9.3%
i 27759
7.6%
r 23435
 
6.4%
o 23395
 
6.4%
l 19298
 
5.3%
h 17411
 
4.7%
Other values (16) 37212
10.1%
Uppercase Letter
ValueCountFrequency (%)
O 15980
20.9%
N 15149
19.8%
A 14449
18.9%
S 8325
10.9%
C 7694
10.1%
G 3958
 
5.2%
B 3245
 
4.2%
M 3172
 
4.1%
P 1964
 
2.6%
I 578
 
0.8%
Other values (13) 1997
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 10312
95.1%
/ 426
 
3.9%
' 104
 
1.0%
. 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
4 1
50.0%
Space Separator
ValueCountFrequency (%)
60279
100.0%
Modifier Letter
ValueCountFrequency (%)
ʻ 442
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 443937
86.1%
Common 71570
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 59587
13.4%
t 46425
10.5%
n 42137
 
9.5%
e 36547
 
8.2%
c 34220
 
7.7%
i 27759
 
6.3%
r 23435
 
5.3%
o 23395
 
5.3%
l 19298
 
4.3%
h 17411
 
3.9%
Other values (39) 113723
25.6%
Common
ValueCountFrequency (%)
60279
84.2%
, 10312
 
14.4%
ʻ 442
 
0.6%
/ 426
 
0.6%
' 104
 
0.1%
- 4
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
. 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 514623
99.8%
Modifier Letters 442
 
0.1%
None 442
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
60279
11.7%
a 59587
11.6%
t 46425
 
9.0%
n 42137
 
8.2%
e 36547
 
7.1%
c 34220
 
6.6%
i 27759
 
5.4%
r 23435
 
4.6%
o 23395
 
4.5%
l 19298
 
3.7%
Other values (46) 141541
27.5%
Modifier Letters
ValueCountFrequency (%)
ʻ 442
100.0%
None
ValueCountFrequency (%)
ā 442
100.0%

islandGroup
Text

Missing 

Distinct535
Distinct (%)0.5%
Missing4403077
Missing (%)97.5%
Memory size34.5 MiB
2025-01-14T11:45:29.841383image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length42
Median length41
Mean length14.86225396
Min length3

Characters and Unicode

Total characters1673252
Distinct characters64
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)0.1%

Sample

1st rowGreater Antilles
2nd rowGreater Antilles
3rd rowElizabeth Islands
4th rowChannel Islands
5th rowGreater Antilles
ValueCountFrequency (%)
antilles 32223
 
12.5%
greater 32220
 
12.5%
islands 23341
 
9.1%
is 19916
 
7.7%
group 16200
 
6.3%
new 7374
 
2.9%
guinea 6014
 
2.3%
channel 5394
 
2.1%
keys 5332
 
2.1%
florida 5071
 
2.0%
Other values (442) 104053
40.5%
2025-01-14T11:45:30.117154image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 168595
 
10.1%
a 153468
 
9.2%
144554
 
8.6%
s 133119
 
8.0%
l 127504
 
7.6%
r 120065
 
7.2%
n 113308
 
6.8%
t 87870
 
5.3%
i 82774
 
4.9%
G 60256
 
3.6%
Other values (54) 481739
28.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1252200
74.8%
Uppercase Letter 250128
 
14.9%
Space Separator 144554
 
8.6%
Other Punctuation 20643
 
1.2%
Open Punctuation 2855
 
0.2%
Close Punctuation 2855
 
0.2%
Dash Punctuation 17
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 168595
13.5%
a 153468
12.3%
s 133119
10.6%
l 127504
10.2%
r 120065
9.6%
n 113308
9.0%
t 87870
7.0%
i 82774
6.6%
u 49516
 
4.0%
d 48781
 
3.9%
Other values (18) 167200
13.4%
Uppercase Letter
ValueCountFrequency (%)
G 60256
24.1%
I 47120
18.8%
A 36666
14.7%
C 15661
 
6.3%
V 13535
 
5.4%
L 11432
 
4.6%
N 9696
 
3.9%
S 8478
 
3.4%
K 6484
 
2.6%
F 6018
 
2.4%
Other values (16) 34782
13.9%
Other Punctuation
ValueCountFrequency (%)
. 19898
96.4%
' 710
 
3.4%
, 30
 
0.1%
? 5
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
[ 1851
64.8%
( 1004
35.2%
Close Punctuation
ValueCountFrequency (%)
] 1851
64.8%
) 1004
35.2%
Space Separator
ValueCountFrequency (%)
144554
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1502328
89.8%
Common 170924
 
10.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 168595
11.2%
a 153468
 
10.2%
s 133119
 
8.9%
l 127504
 
8.5%
r 120065
 
8.0%
n 113308
 
7.5%
t 87870
 
5.8%
i 82774
 
5.5%
G 60256
 
4.0%
u 49516
 
3.3%
Other values (44) 405853
27.0%
Common
ValueCountFrequency (%)
144554
84.6%
. 19898
 
11.6%
[ 1851
 
1.1%
] 1851
 
1.1%
( 1004
 
0.6%
) 1004
 
0.6%
' 710
 
0.4%
, 30
 
< 0.1%
- 17
 
< 0.1%
? 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1664297
99.5%
None 8955
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 168595
 
10.1%
a 153468
 
9.2%
144554
 
8.7%
s 133119
 
8.0%
l 127504
 
7.7%
r 120065
 
7.2%
n 113308
 
6.8%
t 87870
 
5.3%
i 82774
 
5.0%
G 60256
 
3.6%
Other values (51) 472784
28.4%
None
ValueCountFrequency (%)
Î 4724
52.8%
á 4230
47.2%
ñ 1
 
< 0.1%

island
Text

Missing 

Distinct4293
Distinct (%)1.1%
Missing4139168
Missing (%)91.7%
Memory size34.5 MiB
2025-01-14T11:45:30.320465image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length48
Median length43
Mean length9.545619706
Min length1

Characters and Unicode

Total characters3593859
Distinct characters86
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1311 ?
Unique (%)0.3%

Sample

1st rowRota
2nd rowHispaniola
3rd rowNorth Island
4th rowKaua'i
5th rowHispaniola Island
ValueCountFrequency (%)
hispaniola 49160
 
8.5%
island 45105
 
7.8%
cuba 23045
 
4.0%
oahu 17038
 
2.9%
st 12448
 
2.2%
kaua'i 12005
 
2.1%
new 10482
 
1.8%
isla 9883
 
1.7%
jamaica 9865
 
1.7%
luzon 9652
 
1.7%
Other values (3257) 379339
65.6%
2025-01-14T11:45:30.605856image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 572883
15.9%
i 282904
 
7.9%
n 241731
 
6.7%
o 215280
 
6.0%
201529
 
5.6%
l 189222
 
5.3%
u 174379
 
4.9%
e 170799
 
4.8%
s 161533
 
4.5%
r 127280
 
3.5%
Other values (76) 1256319
35.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2754132
76.6%
Uppercase Letter 562682
 
15.7%
Space Separator 201529
 
5.6%
Other Punctuation 42453
 
1.2%
Close Punctuation 15796
 
0.4%
Open Punctuation 15786
 
0.4%
Dash Punctuation 1476
 
< 0.1%
Decimal Number 4
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 572883
20.8%
i 282904
10.3%
n 241731
8.8%
o 215280
 
7.8%
l 189222
 
6.9%
u 174379
 
6.3%
e 170799
 
6.2%
s 161533
 
5.9%
r 127280
 
4.6%
t 109023
 
4.0%
Other values (32) 509098
18.5%
Uppercase Letter
ValueCountFrequency (%)
H 73966
13.1%
I 67946
12.1%
C 61093
 
10.9%
S 44330
 
7.9%
M 34219
 
6.1%
T 25587
 
4.5%
B 25543
 
4.5%
G 25041
 
4.5%
K 23090
 
4.1%
O 22999
 
4.1%
Other values (19) 158868
28.2%
Other Punctuation
ValueCountFrequency (%)
' 20682
48.7%
. 20243
47.7%
, 1360
 
3.2%
? 155
 
0.4%
/ 12
 
< 0.1%
& 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
[ 13359
84.6%
( 2427
 
15.4%
Close Punctuation
ValueCountFrequency (%)
] 13357
84.6%
) 2439
 
15.4%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
6 2
50.0%
Space Separator
ValueCountFrequency (%)
201529
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1476
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3316814
92.3%
Common 277045
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 572883
17.3%
i 282904
 
8.5%
n 241731
 
7.3%
o 215280
 
6.5%
l 189222
 
5.7%
u 174379
 
5.3%
e 170799
 
5.1%
s 161533
 
4.9%
r 127280
 
3.8%
t 109023
 
3.3%
Other values (61) 1071780
32.3%
Common
ValueCountFrequency (%)
201529
72.7%
' 20682
 
7.5%
. 20243
 
7.3%
[ 13359
 
4.8%
] 13357
 
4.8%
) 2439
 
0.9%
( 2427
 
0.9%
- 1476
 
0.5%
, 1360
 
0.5%
? 155
 
0.1%
Other values (5) 18
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3587365
99.8%
None 6494
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 572883
16.0%
i 282904
 
7.9%
n 241731
 
6.7%
o 215280
 
6.0%
201529
 
5.6%
l 189222
 
5.3%
u 174379
 
4.9%
e 170799
 
4.8%
s 161533
 
4.5%
r 127280
 
3.5%
Other values (56) 1249825
34.8%
None
ValueCountFrequency (%)
ç 1813
27.9%
Î 1610
24.8%
é 899
13.8%
ó 801
12.3%
á 452
 
7.0%
â 387
 
6.0%
ñ 238
 
3.7%
ã 150
 
2.3%
Ö 58
 
0.9%
í 35
 
0.5%
Other values (10) 51
 
0.8%

country
Text

Distinct460
Distinct (%)< 0.1%
Missing38684
Missing (%)0.9%
Memory size34.5 MiB
2025-01-14T11:45:30.813289image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length51
Median length50
Mean length9.388789355
Min length4

Characters and Unicode

Total characters42033394
Distinct characters65
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)< 0.1%

Sample

1st rowUnited States
2nd rowPeru
3rd rowArgentina
4th rowVenezuela
5th rowSouth Africa
ValueCountFrequency (%)
united 1351629
21.1%
states 1342475
21.0%
brazil 299921
 
4.7%
mexico 290196
 
4.5%
colombia 165032
 
2.6%
venezuela 119690
 
1.9%
peru 116267
 
1.8%
canada 113187
 
1.8%
china 108364
 
1.7%
ecuador 89292
 
1.4%
Other values (309) 2403309
37.6%
2025-01-14T11:45:31.086544image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5086492
12.1%
t 4552689
 
10.8%
e 4466872
 
10.6%
i 3789420
 
9.0%
n 3120571
 
7.4%
d 1943611
 
4.6%
1922385
 
4.6%
s 1851829
 
4.4%
S 1538403
 
3.7%
U 1421487
 
3.4%
Other values (55) 12339635
29.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 33687190
80.1%
Uppercase Letter 6371529
 
15.2%
Space Separator 1922385
 
4.6%
Other Punctuation 46937
 
0.1%
Dash Punctuation 4237
 
< 0.1%
Close Punctuation 558
 
< 0.1%
Open Punctuation 558
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 5086492
15.1%
t 4552689
13.5%
e 4466872
13.3%
i 3789420
11.2%
n 3120571
9.3%
d 1943611
 
5.8%
s 1851829
 
5.5%
o 1417591
 
4.2%
r 1215020
 
3.6%
l 1213250
 
3.6%
Other values (20) 5029845
14.9%
Uppercase Letter
ValueCountFrequency (%)
S 1538403
24.1%
U 1421487
22.3%
C 581180
 
9.1%
B 414386
 
6.5%
P 408939
 
6.4%
M 379429
 
6.0%
G 256961
 
4.0%
R 184136
 
2.9%
A 180790
 
2.8%
I 146545
 
2.3%
Other values (15) 859273
13.5%
Other Punctuation
ValueCountFrequency (%)
. 25759
54.9%
, 18129
38.6%
/ 2903
 
6.2%
? 146
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 482
86.4%
] 76
 
13.6%
Open Punctuation
ValueCountFrequency (%)
( 482
86.4%
[ 76
 
13.6%
Space Separator
ValueCountFrequency (%)
1922385
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4237
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40058719
95.3%
Common 1974675
 
4.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 5086492
12.7%
t 4552689
11.4%
e 4466872
11.2%
i 3789420
 
9.5%
n 3120571
 
7.8%
d 1943611
 
4.9%
s 1851829
 
4.6%
S 1538403
 
3.8%
U 1421487
 
3.5%
o 1417591
 
3.5%
Other values (45) 10869754
27.1%
Common
ValueCountFrequency (%)
1922385
97.4%
. 25759
 
1.3%
, 18129
 
0.9%
- 4237
 
0.2%
/ 2903
 
0.1%
) 482
 
< 0.1%
( 482
 
< 0.1%
? 146
 
< 0.1%
[ 76
 
< 0.1%
] 76
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42027851
> 99.9%
None 5543
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 5086492
12.1%
t 4552689
 
10.8%
e 4466872
 
10.6%
i 3789420
 
9.0%
n 3120571
 
7.4%
d 1943611
 
4.6%
1922385
 
4.6%
s 1851829
 
4.4%
S 1538403
 
3.7%
U 1421487
 
3.4%
Other values (51) 12334092
29.3%
None
ValueCountFrequency (%)
é 3137
56.6%
ç 2098
37.8%
á 236
 
4.3%
ã 72
 
1.3%

countryCode
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing4515660
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:31.147076image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row1872
ValueCountFrequency (%)
1872 1
100.0%
2025-01-14T11:45:31.245411image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
25.0%
8 1
25.0%
7 1
25.0%
2 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
25.0%
8 1
25.0%
7 1
25.0%
2 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
25.0%
8 1
25.0%
7 1
25.0%
2 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
25.0%
8 1
25.0%
7 1
25.0%
2 1
25.0%

stateProvince
Text

Missing 

Distinct4563
Distinct (%)0.1%
Missing1002183
Missing (%)22.2%
Memory size34.5 MiB
2025-01-14T11:45:31.430861image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length51
Mean length9.008130405
Min length1

Characters and Unicode

Total characters31649868
Distinct characters144
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1056 ?
Unique (%)< 0.1%

Sample

1st rowFlorida
2nd rowPiura
3rd rowFormosa
4th rowCarabobo
5th rowManabí
ValueCountFrequency (%)
california 201997
 
4.4%
new 105413
 
2.3%
florida 88714
 
1.9%
virginia 72232
 
1.6%
texas 71235
 
1.5%
alaska 67186
 
1.5%
amazonas 60909
 
1.3%
hawaii 55246
 
1.2%
san 50578
 
1.1%
arizona 50395
 
1.1%
Other values (3812) 3798781
82.2%
2025-01-14T11:45:31.710098image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4911736
15.5%
i 2591410
 
8.2%
n 2327641
 
7.4%
o 2312232
 
7.3%
r 2011322
 
6.4%
e 1596527
 
5.0%
s 1274100
 
4.0%
l 1254624
 
4.0%
t 1112877
 
3.5%
1109208
 
3.5%
Other values (134) 11148191
35.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 25675252
81.1%
Uppercase Letter 4615949
 
14.6%
Space Separator 1109208
 
3.5%
Dash Punctuation 117663
 
0.4%
Other Punctuation 86259
 
0.3%
Open Punctuation 22735
 
0.1%
Close Punctuation 22735
 
0.1%
Modifier Letter 59
 
< 0.1%
Decimal Number 6
 
< 0.1%
Modifier Symbol 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4911736
19.1%
i 2591410
10.1%
n 2327641
9.1%
o 2312232
9.0%
r 2011322
 
7.8%
e 1596527
 
6.2%
s 1274100
 
5.0%
l 1254624
 
4.9%
t 1112877
 
4.3%
u 1059938
 
4.1%
Other values (72) 5222845
20.3%
Uppercase Letter
ValueCountFrequency (%)
C 714018
15.5%
M 451601
 
9.8%
S 382515
 
8.3%
A 361688
 
7.8%
N 307507
 
6.7%
P 258383
 
5.6%
T 197076
 
4.3%
B 180196
 
3.9%
V 178962
 
3.9%
L 157384
 
3.4%
Other values (34) 1426619
30.9%
Other Punctuation
ValueCountFrequency (%)
. 64175
74.4%
/ 13649
 
15.8%
, 4058
 
4.7%
' 3620
 
4.2%
? 639
 
0.7%
& 118
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 21809
95.9%
] 925
 
4.1%
} 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 21809
95.9%
[ 926
 
4.1%
Decimal Number
ValueCountFrequency (%)
3 4
66.7%
7 2
33.3%
Modifier Symbol
ValueCountFrequency (%)
¸ 1
50.0%
´ 1
50.0%
Space Separator
ValueCountFrequency (%)
1109208
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 117663
100.0%
Modifier Letter
ValueCountFrequency (%)
ʼ 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 30291201
95.7%
Common 1358667
 
4.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4911736
16.2%
i 2591410
 
8.6%
n 2327641
 
7.7%
o 2312232
 
7.6%
r 2011322
 
6.6%
e 1596527
 
5.3%
s 1274100
 
4.2%
l 1254624
 
4.1%
t 1112877
 
3.7%
u 1059938
 
3.5%
Other values (116) 9838794
32.5%
Common
ValueCountFrequency (%)
1109208
81.6%
- 117663
 
8.7%
. 64175
 
4.7%
( 21809
 
1.6%
) 21809
 
1.6%
/ 13649
 
1.0%
, 4058
 
0.3%
' 3620
 
0.3%
[ 926
 
0.1%
] 925
 
0.1%
Other values (8) 825
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31262419
98.8%
None 387356
 
1.2%
Modifier Letters 59
 
< 0.1%
Latin Ext Additional 34
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4911736
15.7%
i 2591410
 
8.3%
n 2327641
 
7.4%
o 2312232
 
7.4%
r 2011322
 
6.4%
e 1596527
 
5.1%
s 1274100
 
4.1%
l 1254624
 
4.0%
t 1112877
 
3.6%
1109208
 
3.5%
Other values (57) 10760742
34.4%
None
ValueCountFrequency (%)
á 140128
36.2%
í 81452
21.0%
é 62681
16.2%
ó 43934
 
11.3%
ã 21483
 
5.5%
ô 12517
 
3.2%
ñ 5935
 
1.5%
ü 4328
 
1.1%
ä 2589
 
0.7%
ö 2183
 
0.6%
Other values (54) 10126
 
2.6%
Modifier Letters
ValueCountFrequency (%)
ʼ 59
100.0%
Latin Ext Additional
ValueCountFrequency (%)
ḍ 10
29.4%
ṭ 8
23.5%
ồ 3
 
8.8%
ộ 2
 
5.9%
ế 2
 
5.9%
ả 2
 
5.9%
ị 2
 
5.9%
ẵ 1
 
2.9%
ừ 1
 
2.9%
ậ 1
 
2.9%
Other values (2) 2
 
5.9%

county
Text

Missing 

Distinct12276
Distinct (%)1.7%
Missing3778676
Missing (%)83.7%
Memory size34.5 MiB
2025-01-14T11:45:31.909688image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length56
Median length49
Mean length9.15335726
Min length1

Characters and Unicode

Total characters6745887
Distinct characters111
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3590 ?
Unique (%)0.5%

Sample

1st rowParroquia
2nd rowDuval
3rd rowBoulder
4th rowCantal
5th rowArlington
ValueCountFrequency (%)
county 55931
 
5.4%
san 32851
 
3.2%
prince 19199
 
1.9%
honolulu 19178
 
1.8%
santa 18068
 
1.7%
los 14015
 
1.4%
angeles 13830
 
1.3%
montgomery 13792
 
1.3%
george's 13723
 
1.3%
maui 12914
 
1.2%
Other values (9383) 823511
79.4%
2025-01-14T11:45:32.181980image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 769422
 
11.4%
o 546391
 
8.1%
n 533923
 
7.9%
e 515856
 
7.6%
r 422472
 
6.3%
i 392542
 
5.8%
t 309386
 
4.6%
u 307150
 
4.6%
300027
 
4.4%
l 289660
 
4.3%
Other values (101) 2359058
35.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5401031
80.1%
Uppercase Letter 1011313
 
15.0%
Space Separator 300027
 
4.4%
Other Punctuation 25581
 
0.4%
Dash Punctuation 6153
 
0.1%
Close Punctuation 782
 
< 0.1%
Open Punctuation 781
 
< 0.1%
Modifier Symbol 122
 
< 0.1%
Decimal Number 93
 
< 0.1%
Nonspacing Mark 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 769422
14.2%
o 546391
10.1%
n 533923
9.9%
e 515856
9.6%
r 422472
 
7.8%
i 392542
 
7.3%
t 309386
 
5.7%
u 307150
 
5.7%
l 289660
 
5.4%
s 242628
 
4.5%
Other values (38) 1071601
19.8%
Uppercase Letter
ValueCountFrequency (%)
C 150693
14.9%
S 110876
11.0%
M 104694
 
10.4%
B 69270
 
6.8%
P 63056
 
6.2%
A 60055
 
5.9%
H 55148
 
5.5%
L 50422
 
5.0%
G 40017
 
4.0%
F 34703
 
3.4%
Other values (28) 272379
26.9%
Other Punctuation
ValueCountFrequency (%)
' 15573
60.9%
. 5768
 
22.5%
/ 3392
 
13.3%
? 562
 
2.2%
, 248
 
1.0%
& 20
 
0.1%
; 9
 
< 0.1%
\ 4
 
< 0.1%
: 3
 
< 0.1%
¡ 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 46
49.5%
2 44
47.3%
6 1
 
1.1%
4 1
 
1.1%
9 1
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 6150
> 99.9%
– 3
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 717
91.8%
[ 64
 
8.2%
Close Punctuation
ValueCountFrequency (%)
) 717
91.7%
] 65
 
8.3%
Space Separator
ValueCountFrequency (%)
300027
100.0%
Modifier Symbol
ValueCountFrequency (%)
´ 122
100.0%
Nonspacing Mark
ValueCountFrequency (%)
́ 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6412344
95.1%
Common 333540
 
4.9%
Inherited 3
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 769422
 
12.0%
o 546391
 
8.5%
n 533923
 
8.3%
e 515856
 
8.0%
r 422472
 
6.6%
i 392542
 
6.1%
t 309386
 
4.8%
u 307150
 
4.8%
l 289660
 
4.5%
s 242628
 
3.8%
Other values (76) 2082914
32.5%
Common
ValueCountFrequency (%)
300027
90.0%
' 15573
 
4.7%
- 6150
 
1.8%
. 5768
 
1.7%
/ 3392
 
1.0%
( 717
 
0.2%
) 717
 
0.2%
? 562
 
0.2%
, 248
 
0.1%
´ 122
 
< 0.1%
Other values (14) 264
 
0.1%
Inherited
ValueCountFrequency (%)
́ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6684490
99.1%
None 61391
 
0.9%
Punctuation 3
 
< 0.1%
Diacriticals 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 769422
 
11.5%
o 546391
 
8.2%
n 533923
 
8.0%
e 515856
 
7.7%
r 422472
 
6.3%
i 392542
 
5.9%
t 309386
 
4.6%
u 307150
 
4.6%
300027
 
4.5%
l 289660
 
4.3%
Other values (63) 2297661
34.4%
None
ValueCountFrequency (%)
á 13327
21.7%
é 10282
16.7%
í 10031
16.3%
ó 8697
14.2%
ã 7050
11.5%
ç 4342
 
7.1%
è 1366
 
2.2%
ô 1253
 
2.0%
ñ 1116
 
1.8%
ê 942
 
1.5%
Other values (26) 2985
 
4.9%
Punctuation
ValueCountFrequency (%)
– 3
100.0%
Diacriticals
ValueCountFrequency (%)
́ 3
100.0%

locality
Text

Missing 

Distinct2190202
Distinct (%)52.4%
Missing332028
Missing (%)7.4%
Memory size34.5 MiB
2025-01-14T11:45:32.712878image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length239546
Median length438
Mean length47.49715737
Min length1

Characters and Unicode

Total characters198710675
Distinct characters424
Distinct categories21 ?
Distinct scripts6 ?
Distinct blocks22 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1771025 ?
Unique (%)42.3%

Sample

1st rowGulf of Mexico
2nd rowDept. Piura: Ayabaca
3rd rowDep. Pilcomayo. al E a 2 Km de P. Porteño.
4th rowSelva siempre verde en las quebradas al norte de Los Tanques, arriba de la Planta Eléctrica, en las cabeceras del Río San Gián, al sur de Borburata.
5th rowFlat terrain near Skukuza rest camp, Kruger National Park.
ValueCountFrequency (%)
of 1585417
 
5.0%
de 609558
 
1.9%
the 376944
 
1.2%
km 372123
 
1.2%
near 341319
 
1.1%
and 273717
 
0.9%
on 273627
 
0.9%
in 261704
 
0.8%
county 254734
 
0.8%
la 230318
 
0.7%
Other values (599581) 26894148
85.4%
2025-01-14T11:45:33.455966image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27250345
 
13.7%
a 18162578
 
9.1%
e 14022740
 
7.1%
o 13213905
 
6.6%
n 11023738
 
5.5%
i 10220547
 
5.1%
r 10113701
 
5.1%
t 8788622
 
4.4%
l 7107480
 
3.6%
s 6902603
 
3.5%
Other values (414) 71904416
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 137188370
69.0%
Space Separator 27250345
 
13.7%
Uppercase Letter 20470547
 
10.3%
Other Punctuation 9991899
 
5.0%
Decimal Number 2289002
 
1.2%
Dash Punctuation 522521
 
0.3%
Open Punctuation 365371
 
0.2%
Close Punctuation 362506
 
0.2%
Control 218330
 
0.1%
Other Number 19102
 
< 0.1%
Other values (11) 32682
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 18162578
13.2%
e 14022740
10.2%
o 13213905
9.6%
n 11023738
 
8.0%
i 10220547
 
7.5%
r 10113701
 
7.4%
t 8788622
 
6.4%
l 7107480
 
5.2%
s 6902603
 
5.0%
u 5110133
 
3.7%
Other values (168) 32522323
23.7%
Uppercase Letter
ValueCountFrequency (%)
C 2415927
 
11.8%
S 2030001
 
9.9%
M 1536549
 
7.5%
P 1504174
 
7.3%
R 1298250
 
6.3%
B 1168884
 
5.7%
A 1036363
 
5.1%
N 1025732
 
5.0%
L 921587
 
4.5%
T 846871
 
4.1%
Other values (85) 6686209
32.7%
Other Punctuation
ValueCountFrequency (%)
. 5595503
56.0%
, 3400184
34.0%
: 451617
 
4.5%
; 188440
 
1.9%
' 148212
 
1.5%
" 97269
 
1.0%
/ 49749
 
0.5%
& 41165
 
0.4%
# 9097
 
0.1%
? 7631
 
0.1%
Other values (12) 3032
 
< 0.1%
Other Symbol
ValueCountFrequency (%)
° 6828
99.2%
├ 18
 
0.3%
░ 6
 
0.1%
┬ 6
 
0.1%
¦ 5
 
0.1%
│ 3
 
< 0.1%
─ 3
 
< 0.1%
▒ 2
 
< 0.1%
☼ 2
 
< 0.1%
™ 2
 
< 0.1%
Other values (5) 5
 
0.1%
Control
ValueCountFrequency (%)
216904
99.3%
1148
 
0.5%
 71
 
< 0.1%
 65
 
< 0.1%
 39
 
< 0.1%
 31
 
< 0.1%
 30
 
< 0.1%
 27
 
< 0.1%
 9
 
< 0.1%
 2
 
< 0.1%
Other values (3) 4
 
< 0.1%
Other Number
ValueCountFrequency (%)
½ 12766
66.8%
¼ 5486
28.7%
¾ 693
 
3.6%
² 70
 
0.4%
⅓ 52
 
0.3%
⅛ 15
 
0.1%
⅔ 6
 
< 0.1%
³ 6
 
< 0.1%
⅜ 4
 
< 0.1%
¹ 2
 
< 0.1%
Other values (2) 2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
= 7069
37.6%
± 5350
28.5%
+ 3005
16.0%
> 1166
 
6.2%
< 1123
 
6.0%
~ 1026
 
5.5%
| 39
 
0.2%
→ 12
 
0.1%
∆ 8
 
< 0.1%
↔ 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 471051
20.6%
2 325524
14.2%
0 281269
12.3%
5 270344
11.8%
3 241514
10.6%
4 188715
8.2%
6 149071
 
6.5%
8 126175
 
5.5%
7 123405
 
5.4%
9 111934
 
4.9%
Modifier Letter
ValueCountFrequency (%)
ʻ 442
96.5%
ᵉ 7
 
1.5%
ˮ 2
 
0.4%
ᵍ 1
 
0.2%
ᶵ 1
 
0.2%
ᵈ 1
 
0.2%
ˍ 1
 
0.2%
ʼ 1
 
0.2%
ᴸ 1
 
0.2%
ᴱ 1
 
0.2%
Other Letter
ValueCountFrequency (%)
º 3444
97.1%
ª 95
 
2.7%
林 1
 
< 0.1%
大 1
 
< 0.1%
道 1
 
< 0.1%
郡 1
 
< 0.1%
角 1
 
< 0.1%
平 1
 
< 0.1%
太 1
 
< 0.1%
Nonspacing Mark
ValueCountFrequency (%)
ͤ 9
32.1%
̄ 6
21.4%
̈ 4
14.3%
̋ 3
 
10.7%
̩ 2
 
7.1%
́ 1
 
3.6%
̌ 1
 
3.6%
᷉ 1
 
3.6%
̊ 1
 
3.6%
Format
ValueCountFrequency (%)
­ 7
30.4%
‏ 3
13.0%
‭ 3
13.0%
‎ 2
 
8.7%
 2
 
8.7%
​ 2
 
8.7%
 2
 
8.7%
‌ 2
 
8.7%
Modifier Symbol
ValueCountFrequency (%)
´ 491
90.1%
¨ 32
 
5.9%
^ 11
 
2.0%
˶ 5
 
0.9%
˚ 3
 
0.6%
˜ 2
 
0.4%
¯ 1
 
0.2%
Currency Symbol
ValueCountFrequency (%)
¢ 114
46.5%
¤ 96
39.2%
$ 19
 
7.8%
£ 14
 
5.7%
¥ 1
 
0.4%
€ 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 269825
73.8%
[ 94852
 
26.0%
„ 402
 
0.1%
‚ 198
 
0.1%
{ 94
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 522467
> 99.9%
– 36
 
< 0.1%
— 18
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 267308
73.7%
] 95098
 
26.2%
} 100
 
< 0.1%
Final Punctuation
ValueCountFrequency (%)
» 802
93.0%
” 46
 
5.3%
› 14
 
1.6%
Initial Punctuation
ValueCountFrequency (%)
« 792
83.2%
“ 159
 
16.7%
‛ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
27250345
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 343
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 157662328
79.3%
Common 41048170
 
20.7%
Greek 137
 
< 0.1%
Inherited 30
 
< 0.1%
Han 7
 
< 0.1%
Cyrillic 3
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 18162578
 
11.5%
e 14022740
 
8.9%
o 13213905
 
8.4%
n 11023738
 
7.0%
i 10220547
 
6.5%
r 10113701
 
6.4%
t 8788622
 
5.6%
l 7107480
 
4.5%
s 6902603
 
4.4%
u 5110133
 
3.2%
Other values (250) 52996281
33.6%
Common
ValueCountFrequency (%)
27250345
66.4%
. 5595503
 
13.6%
, 3400184
 
8.3%
- 522467
 
1.3%
1 471051
 
1.1%
: 451617
 
1.1%
2 325524
 
0.8%
0 281269
 
0.7%
5 270344
 
0.7%
( 269825
 
0.7%
Other values (116) 2210041
 
5.4%
Greek
ValueCountFrequency (%)
λ 26
19.0%
ν 21
15.3%
η 15
10.9%
ή 13
9.5%
υ 13
9.5%
Κ 13
9.5%
ρ 7
 
5.1%
α 4
 
2.9%
ο 4
 
2.9%
ά 3
 
2.2%
Other values (8) 18
13.1%
Inherited
ValueCountFrequency (%)
ͤ 9
30.0%
̄ 6
20.0%
̈ 4
13.3%
̋ 3
 
10.0%
‌ 2
 
6.7%
̩ 2
 
6.7%
́ 1
 
3.3%
̌ 1
 
3.3%
᷉ 1
 
3.3%
̊ 1
 
3.3%
Han
ValueCountFrequency (%)
林 1
14.3%
大 1
14.3%
道 1
14.3%
郡 1
14.3%
角 1
14.3%
平 1
14.3%
太 1
14.3%
Cyrillic
ValueCountFrequency (%)
ҫ 1
33.3%
ӧ 1
33.3%
ӗ 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 197800565
99.5%
None 908364
 
0.5%
Punctuation 1039
 
< 0.1%
Modifier Letters 456
 
< 0.1%
Number Forms 79
 
< 0.1%
Latin Ext Additional 46
 
< 0.1%
Box Drawing 33
 
< 0.1%
Diacriticals 27
 
< 0.1%
Arrows 13
 
< 0.1%
Phonetic Ext 11
 
< 0.1%
Other values (12) 42
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27250345
 
13.8%
a 18162578
 
9.2%
e 14022740
 
7.1%
o 13213905
 
6.7%
n 11023738
 
5.6%
i 10220547
 
5.2%
r 10113701
 
5.1%
t 8788622
 
4.4%
l 7107480
 
3.6%
s 6902603
 
3.5%
Other values (90) 70994306
35.9%
None
ValueCountFrequency (%)
í 211195
23.3%
á 166897
18.4%
é 110126
12.1%
ó 93913
10.3%
ñ 46099
 
5.1%
ã 36696
 
4.0%
ú 26716
 
2.9%
ç 22907
 
2.5%
ü 18482
 
2.0%
ä 16954
 
1.9%
Other values (221) 158379
17.4%
Modifier Letters
ValueCountFrequency (%)
ʻ 442
96.9%
˶ 5
 
1.1%
˚ 3
 
0.7%
ˮ 2
 
0.4%
˜ 2
 
0.4%
ˍ 1
 
0.2%
ʼ 1
 
0.2%
Punctuation
ValueCountFrequency (%)
„ 402
38.7%
‚ 198
19.1%
“ 159
 
15.3%
… 149
 
14.3%
” 46
 
4.4%
– 36
 
3.5%
— 18
 
1.7%
› 14
 
1.3%
‏ 3
 
0.3%
‭ 3
 
0.3%
Other values (7) 11
 
1.1%
Number Forms
ValueCountFrequency (%)
⅓ 52
65.8%
⅛ 15
 
19.0%
⅔ 6
 
7.6%
⅜ 4
 
5.1%
⅕ 1
 
1.3%
⅝ 1
 
1.3%
Box Drawing
ValueCountFrequency (%)
├ 18
54.5%
┬ 6
 
18.2%
│ 3
 
9.1%
─ 3
 
9.1%
┼ 1
 
3.0%
║ 1
 
3.0%
╢ 1
 
3.0%
Arrows
ValueCountFrequency (%)
→ 12
92.3%
↔ 1
 
7.7%
Latin Ext Additional
ValueCountFrequency (%)
ṅ 9
19.6%
ắ 7
15.2%
ị 4
8.7%
ḗ 4
8.7%
ẽ 3
 
6.5%
ḿ 3
 
6.5%
ṁ 2
 
4.3%
ạ 2
 
4.3%
ẑ 2
 
4.3%
ộ 2
 
4.3%
Other values (7) 8
17.4%
Diacriticals
ValueCountFrequency (%)
ͤ 9
33.3%
̄ 6
22.2%
̈ 4
14.8%
̋ 3
 
11.1%
̩ 2
 
7.4%
́ 1
 
3.7%
̌ 1
 
3.7%
̊ 1
 
3.7%
Math Operators
ValueCountFrequency (%)
∆ 8
100.0%
Phonetic Ext
ValueCountFrequency (%)
ᵉ 7
63.6%
ᵍ 1
 
9.1%
ᵈ 1
 
9.1%
ᴸ 1
 
9.1%
ᴱ 1
 
9.1%
Block Elements
ValueCountFrequency (%)
░ 6
75.0%
▒ 2
 
25.0%
IPA Ext
ValueCountFrequency (%)
ɶ 3
60.0%
ɐ 1
 
20.0%
ʈ 1
 
20.0%
Greek Ext
ValueCountFrequency (%)
ῡ 2
66.7%
ᾰ 1
33.3%
Misc Symbols
ValueCountFrequency (%)
☼ 2
100.0%
Letterlike Symbols
ValueCountFrequency (%)
™ 2
100.0%
Cyrillic
ValueCountFrequency (%)
ҫ 1
33.3%
ӧ 1
33.3%
ӗ 1
33.3%
CJK
ValueCountFrequency (%)
林 1
14.3%
大 1
14.3%
道 1
14.3%
郡 1
14.3%
角 1
14.3%
平 1
14.3%
太 1
14.3%
Diacriticals Sup
ValueCountFrequency (%)
᷉ 1
100.0%
Phonetic Ext Sup
ValueCountFrequency (%)
ᶵ 1
100.0%
Currency Symbols
ValueCountFrequency (%)
€ 1
100.0%
Misc Technical
ValueCountFrequency (%)
⌐ 1
100.0%

verbatimLocality
Text

Missing 

Distinct5
Distinct (%)100.0%
Missing4515656
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:33.530550image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.4
Min length10

Characters and Unicode

Total characters52
Distinct characters12
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row83 41'11"W
2nd row78 50' 50" W
3rd row82 44'01"W
4th row82 43'07"W
5th row83 37'47"W
ValueCountFrequency (%)
83 2
16.7%
50 2
16.7%
82 2
16.7%
41'11"w 1
8.3%
78 1
8.3%
w 1
8.3%
44'01"w 1
8.3%
43'07"w 1
8.3%
37'47"w 1
8.3%
2025-01-14T11:45:33.649794image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
13.5%
8 5
9.6%
4 5
9.6%
' 5
9.6%
" 5
9.6%
W 5
9.6%
3 4
7.7%
1 4
7.7%
7 4
7.7%
0 4
7.7%
Other values (2) 4
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
57.7%
Other Punctuation 10
 
19.2%
Space Separator 7
 
13.5%
Uppercase Letter 5
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 5
16.7%
4 5
16.7%
3 4
13.3%
1 4
13.3%
7 4
13.3%
0 4
13.3%
5 2
 
6.7%
2 2
 
6.7%
Other Punctuation
ValueCountFrequency (%)
' 5
50.0%
" 5
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Uppercase Letter
ValueCountFrequency (%)
W 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47
90.4%
Latin 5
 
9.6%

Most frequent character per script

Common
ValueCountFrequency (%)
7
14.9%
8 5
10.6%
4 5
10.6%
' 5
10.6%
" 5
10.6%
3 4
8.5%
1 4
8.5%
7 4
8.5%
0 4
8.5%
5 2
 
4.3%
Latin
ValueCountFrequency (%)
W 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
13.5%
8 5
9.6%
4 5
9.6%
' 5
9.6%
" 5
9.6%
W 5
9.6%
3 4
7.7%
1 4
7.7%
7 4
7.7%
0 4
7.7%
Other values (2) 4
7.7%

minimumElevationInMeters
Text

Missing 

Distinct4970
Distinct (%)0.3%
Missing2860984
Missing (%)63.4%
Memory size34.5 MiB
2025-01-14T11:45:33.858014image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length9
Mean length5.339273465
Min length3

Characters and Unicode

Total characters8834773
Distinct characters27
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique773 ?
Unique (%)< 0.1%

Sample

1st row2742.0
2nd row750.0
3rd row50.0
4th row0.0
5th row17.0
ValueCountFrequency (%)
100.0 34114
 
2.1%
1000.0 33132
 
2.0%
200.0 29727
 
1.8%
300.0 26699
 
1.6%
500.0 26609
 
1.6%
1500.0 25888
 
1.6%
800.0 25536
 
1.5%
400.0 23967
 
1.4%
900.0 23544
 
1.4%
1200.0 23149
 
1.4%
Other values (4932) 1382314
83.5%
2025-01-14T11:45:34.149036image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3504011
39.7%
. 1654676
18.7%
1 806932
 
9.1%
2 627849
 
7.1%
5 506466
 
5.7%
3 406488
 
4.6%
4 318940
 
3.6%
6 271625
 
3.1%
8 261398
 
3.0%
7 254146
 
2.9%
Other values (17) 222242
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7179762
81.3%
Other Punctuation 1654676
 
18.7%
Dash Punctuation 312
 
< 0.1%
Lowercase Letter 18
 
< 0.1%
Uppercase Letter 3
 
< 0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5
27.8%
s 3
16.7%
n 2
 
11.1%
g 1
 
5.6%
r 1
 
5.6%
i 1
 
5.6%
u 1
 
5.6%
t 1
 
5.6%
c 1
 
5.6%
o 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
0 3504011
48.8%
1 806932
 
11.2%
2 627849
 
8.7%
5 506466
 
7.1%
3 406488
 
5.7%
4 318940
 
4.4%
6 271625
 
3.8%
8 261398
 
3.6%
7 254146
 
3.5%
9 221907
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
D 1
33.3%
M 1
33.3%
S 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 1654676
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 312
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8834752
> 99.9%
Latin 21
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5
23.8%
s 3
14.3%
n 2
 
9.5%
D 1
 
4.8%
g 1
 
4.8%
r 1
 
4.8%
M 1
 
4.8%
i 1
 
4.8%
u 1
 
4.8%
t 1
 
4.8%
Other values (4) 4
19.0%
Common
ValueCountFrequency (%)
0 3504011
39.7%
. 1654676
18.7%
1 806932
 
9.1%
2 627849
 
7.1%
5 506466
 
5.7%
3 406488
 
4.6%
4 318940
 
3.6%
6 271625
 
3.1%
8 261398
 
3.0%
7 254146
 
2.9%
Other values (3) 222221
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8834773
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3504011
39.7%
. 1654676
18.7%
1 806932
 
9.1%
2 627849
 
7.1%
5 506466
 
5.7%
3 406488
 
4.6%
4 318940
 
3.6%
6 271625
 
3.1%
8 261398
 
3.0%
7 254146
 
2.9%
Other values (17) 222242
 
2.5%

maximumElevationInMeters
Text

Missing 

Distinct2856
Distinct (%)0.6%
Missing4017410
Missing (%)89.0%
Memory size34.5 MiB
2025-01-14T11:45:34.373923image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.395878784
Min length3

Characters and Unicode

Total characters2688502
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique706 ?
Unique (%)0.1%

Sample

1st row450.0
2nd row850.0
3rd row792.0
4th row1680.0
5th row1981.0
ValueCountFrequency (%)
1000.0 11909
 
2.4%
600.0 10801
 
2.2%
500.0 10617
 
2.1%
1500.0 10106
 
2.0%
900.0 9847
 
2.0%
1200.0 9380
 
1.9%
100.0 9062
 
1.8%
400.0 8956
 
1.8%
300.0 8472
 
1.7%
2000.0 8255
 
1.7%
Other values (2842) 400846
80.5%
2025-01-14T11:45:34.651550image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1146584
42.6%
. 498251
18.5%
1 224425
 
8.3%
2 185816
 
6.9%
5 156368
 
5.8%
3 121709
 
4.5%
4 85324
 
3.2%
6 75371
 
2.8%
8 70381
 
2.6%
7 65922
 
2.5%
Other values (2) 58351
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2190247
81.5%
Other Punctuation 498251
 
18.5%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1146584
52.3%
1 224425
 
10.2%
2 185816
 
8.5%
5 156368
 
7.1%
3 121709
 
5.6%
4 85324
 
3.9%
6 75371
 
3.4%
8 70381
 
3.2%
7 65922
 
3.0%
9 58347
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 498251
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2688502
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1146584
42.6%
. 498251
18.5%
1 224425
 
8.3%
2 185816
 
6.9%
5 156368
 
5.8%
3 121709
 
4.5%
4 85324
 
3.2%
6 75371
 
2.8%
8 70381
 
2.6%
7 65922
 
2.5%
Other values (2) 58351
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2688502
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1146584
42.6%
. 498251
18.5%
1 224425
 
8.3%
2 185816
 
6.9%
5 156368
 
5.8%
3 121709
 
4.5%
4 85324
 
3.2%
6 75371
 
2.8%
8 70381
 
2.6%
7 65922
 
2.5%
Other values (2) 58351
 
2.2%

minimumDepthInMeters
Text

Missing 

Distinct172
Distinct (%)0.4%
Missing4475632
Missing (%)99.1%
Memory size34.5 MiB
2025-01-14T11:45:34.770242image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.485947688
Min length3

Characters and Unicode

Total characters139539
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)0.2%

Sample

1st row3.0
2nd row21.0
3rd row3.0
4th row9.0
5th row3.0
ValueCountFrequency (%)
3.0 7621
19.0%
9.0 6771
16.9%
15.0 6023
15.0%
21.0 4195
10.5%
0.0 2654
 
6.6%
37.0 2182
 
5.5%
27.0 1874
 
4.7%
2.0 1319
 
3.3%
12.0 1049
 
2.6%
1.0 878
 
2.2%
Other values (161) 5463
13.6%
2025-01-14T11:45:34.935640image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 43497
31.2%
. 40029
28.7%
1 14301
 
10.2%
3 10509
 
7.5%
2 9006
 
6.5%
5 7321
 
5.2%
9 7125
 
5.1%
7 4678
 
3.4%
6 1307
 
0.9%
4 929
 
0.7%
Other values (2) 837
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99509
71.3%
Other Punctuation 40029
28.7%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43497
43.7%
1 14301
 
14.4%
3 10509
 
10.6%
2 9006
 
9.1%
5 7321
 
7.4%
9 7125
 
7.2%
7 4678
 
4.7%
6 1307
 
1.3%
4 929
 
0.9%
8 836
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 40029
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 139539
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 43497
31.2%
. 40029
28.7%
1 14301
 
10.2%
3 10509
 
7.5%
2 9006
 
6.5%
5 7321
 
5.2%
9 7125
 
5.1%
7 4678
 
3.4%
6 1307
 
0.9%
4 929
 
0.7%
Other values (2) 837
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 139539
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 43497
31.2%
. 40029
28.7%
1 14301
 
10.2%
3 10509
 
7.5%
2 9006
 
6.5%
5 7321
 
5.2%
9 7125
 
5.1%
7 4678
 
3.4%
6 1307
 
0.9%
4 929
 
0.7%
Other values (2) 837
 
0.6%

maximumDepthInMeters
Text

Missing 

Distinct80
Distinct (%)0.2%
Missing4478965
Missing (%)99.2%
Memory size34.5 MiB
2025-01-14T11:45:35.017692image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.677785045
Min length3

Characters and Unicode

Total characters134960
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.1%

Sample

1st row3.0
2nd row27.0
3rd row3.0
4th row15.0
5th row9.0
ValueCountFrequency (%)
9.0 5795
15.8%
15.0 5742
15.6%
21.0 5321
14.5%
27.0 4190
11.4%
3.0 3061
8.3%
49.0 1873
 
5.1%
37.0 1753
 
4.8%
14.0 1250
 
3.4%
11.0 1072
 
2.9%
5.0 1049
 
2.9%
Other values (70) 5590
15.2%
2025-01-14T11:45:35.159806image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37406
27.7%
. 36696
27.2%
1 16747
12.4%
2 10958
 
8.1%
9 7822
 
5.8%
5 7226
 
5.4%
7 6969
 
5.2%
3 5009
 
3.7%
4 3586
 
2.7%
6 1850
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 98264
72.8%
Other Punctuation 36696
 
27.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37406
38.1%
1 16747
17.0%
2 10958
 
11.2%
9 7822
 
8.0%
5 7226
 
7.4%
7 6969
 
7.1%
3 5009
 
5.1%
4 3586
 
3.6%
6 1850
 
1.9%
8 691
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 36696
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 134960
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37406
27.7%
. 36696
27.2%
1 16747
12.4%
2 10958
 
8.1%
9 7822
 
5.8%
5 7226
 
5.4%
7 6969
 
5.2%
3 5009
 
3.7%
4 3586
 
2.7%
6 1850
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37406
27.7%
. 36696
27.2%
1 16747
12.4%
2 10958
 
8.1%
9 7822
 
5.8%
5 7226
 
5.4%
7 6969
 
5.2%
3 5009
 
3.7%
4 3586
 
2.7%
6 1850
 
1.4%

verbatimDepth
Text

Missing 

Distinct18
Distinct (%)0.1%
Missing4494022
Missing (%)99.5%
Memory size34.5 MiB
2025-01-14T11:45:35.231412image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length37
Median length3
Mean length3.033874024
Min length2

Characters and Unicode

Total characters65650
Distinct characters34
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)< 0.1%

Sample

1st rowca.
2nd rowca.
3rd rowca.
4th rowca.
5th rowca.
ValueCountFrequency (%)
ca 21589
99.4%
intertidal 57
 
0.3%
mlw 15
 
0.1%
infralittoral 12
 
0.1%
below 6
 
< 0.1%
above 5
 
< 0.1%
low 5
 
< 0.1%
tide 5
 
< 0.1%
feet 2
 
< 0.1%
cay 2
 
< 0.1%
Other values (20) 22
 
0.1%
2025-01-14T11:45:35.363117image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 21682
33.0%
c 21591
32.9%
. 21426
32.6%
t 151
 
0.2%
l 115
 
0.2%
i 97
 
0.1%
e 90
 
0.1%
r 85
 
0.1%
81
 
0.1%
n 70
 
0.1%
Other values (24) 262
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 44081
67.1%
Other Punctuation 21426
32.6%
Space Separator 81
 
0.1%
Uppercase Letter 49
 
0.1%
Decimal Number 6
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 21682
49.2%
c 21591
49.0%
t 151
 
0.3%
l 115
 
0.3%
i 97
 
0.2%
e 90
 
0.2%
r 85
 
0.2%
n 70
 
0.2%
d 65
 
0.1%
o 37
 
0.1%
Other values (11) 98
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
0 2
33.3%
4 1
16.7%
8 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
I 47
95.9%
A 1
 
2.0%
D 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 21426
100.0%
Space Separator
ValueCountFrequency (%)
81
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
< 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 44130
67.2%
Common 21520
32.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 21682
49.1%
c 21591
48.9%
t 151
 
0.3%
l 115
 
0.3%
i 97
 
0.2%
e 90
 
0.2%
r 85
 
0.2%
n 70
 
0.2%
d 65
 
0.1%
I 47
 
0.1%
Other values (14) 137
 
0.3%
Common
ValueCountFrequency (%)
. 21426
99.6%
81
 
0.4%
( 2
 
< 0.1%
) 2
 
< 0.1%
1 2
 
< 0.1%
0 2
 
< 0.1%
- 2
 
< 0.1%
< 1
 
< 0.1%
4 1
 
< 0.1%
8 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 21682
33.0%
c 21591
32.9%
. 21426
32.6%
t 151
 
0.2%
l 115
 
0.2%
i 97
 
0.1%
e 90
 
0.1%
r 85
 
0.1%
81
 
0.1%
n 70
 
0.1%
Other values (24) 262
 
0.4%

decimalLatitude
Text

Missing 

Distinct65348
Distinct (%)9.8%
Missing3845453
Missing (%)85.2%
Memory size34.5 MiB
2025-01-14T11:45:35.570101image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length55
Median length30
Mean length5.797518084
Min length3

Characters and Unicode

Total characters3885543
Distinct characters39
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29342 ?
Unique (%)4.4%

Sample

1st row26.2786
2nd row-35.57
3rd row18.6519
4th row-36.68
5th row5.86667
ValueCountFrequency (%)
38.895 3805
 
0.6%
38.9694 3780
 
0.6%
3.61 1737
 
0.3%
0.83 1704
 
0.3%
9.405 1696
 
0.3%
5.16667 1640
 
0.2%
0.35 1588
 
0.2%
38.8664 1571
 
0.2%
5.2 1487
 
0.2%
12.83 1407
 
0.2%
Other values (59827) 649801
97.0%
2025-01-14T11:45:35.856351image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 670206
17.2%
3 456711
11.8%
1 360359
9.3%
8 332357
8.6%
2 329986
8.5%
5 313169
8.1%
6 300506
7.7%
7 272005
7.0%
4 239301
 
6.2%
9 228861
 
5.9%
Other values (29) 382082
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3026714
77.9%
Other Punctuation 670211
 
17.2%
Dash Punctuation 188539
 
4.9%
Lowercase Letter 60
 
< 0.1%
Uppercase Letter 11
 
< 0.1%
Space Separator 8
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 11
18.3%
i 8
13.3%
n 6
10.0%
r 5
8.3%
o 5
8.3%
e 4
 
6.7%
t 4
 
6.7%
c 4
 
6.7%
s 4
 
6.7%
l 2
 
3.3%
Other values (6) 7
11.7%
Decimal Number
ValueCountFrequency (%)
3 456711
15.1%
1 360359
11.9%
8 332357
11.0%
2 329986
10.9%
5 313169
10.3%
6 300506
9.9%
7 272005
9.0%
4 239301
7.9%
9 228861
7.6%
0 193459
6.4%
Uppercase Letter
ValueCountFrequency (%)
A 2
18.2%
S 2
18.2%
C 1
9.1%
U 1
9.1%
N 1
9.1%
J 1
9.1%
I 1
9.1%
T 1
9.1%
F 1
9.1%
Other Punctuation
ValueCountFrequency (%)
. 670206
> 99.9%
, 5
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 188539
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3885472
> 99.9%
Latin 71
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 11
15.5%
i 8
11.3%
n 6
 
8.5%
r 5
 
7.0%
o 5
 
7.0%
e 4
 
5.6%
t 4
 
5.6%
c 4
 
5.6%
s 4
 
5.6%
l 2
 
2.8%
Other values (15) 18
25.4%
Common
ValueCountFrequency (%)
. 670206
17.2%
3 456711
11.8%
1 360359
9.3%
8 332357
8.6%
2 329986
8.5%
5 313169
8.1%
6 300506
7.7%
7 272005
7.0%
4 239301
 
6.2%
9 228861
 
5.9%
Other values (4) 382011
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3885543
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 670206
17.2%
3 456711
11.8%
1 360359
9.3%
8 332357
8.6%
2 329986
8.5%
5 313169
8.1%
6 300506
7.7%
7 272005
7.0%
4 239301
 
6.2%
9 228861
 
5.9%
Other values (29) 382082
9.8%

decimalLongitude
Text

Missing 

Distinct67040
Distinct (%)10.0%
Missing3845454
Missing (%)85.2%
Memory size34.5 MiB
2025-01-14T11:45:36.083858image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length10
Mean length6.786640545
Min length3

Characters and Unicode

Total characters4548454
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27805 ?
Unique (%)4.1%

Sample

1st row-83.7803
2nd row137.32
3rd row-71.5572
4th row-72.97
5th row-60.5667
ValueCountFrequency (%)
77.0367 3741
 
0.6%
77.1767 3712
 
0.6%
59.4833 2407
 
0.4%
53.2 1746
 
0.3%
79.8635 1622
 
0.2%
52.33 1591
 
0.2%
77.7064 1461
 
0.2%
59.48 1420
 
0.2%
70.95 1409
 
0.2%
88.08 1385
 
0.2%
Other values (62110) 649714
96.9%
2025-01-14T11:45:36.361119image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 670205
14.7%
- 569111
12.5%
7 494921
10.9%
1 399449
8.8%
6 383274
8.4%
5 381184
8.4%
8 322689
7.1%
3 322209
7.1%
9 271258
6.0%
2 262807
 
5.8%
Other values (18) 471347
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3309113
72.8%
Other Punctuation 670205
 
14.7%
Dash Punctuation 569111
 
12.5%
Lowercase Letter 20
 
< 0.1%
Uppercase Letter 4
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 3
15.0%
a 3
15.0%
i 3
15.0%
o 2
10.0%
c 2
10.0%
s 1
 
5.0%
p 1
 
5.0%
l 1
 
5.0%
t 1
 
5.0%
h 1
 
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
7 494921
15.0%
1 399449
12.1%
6 383274
11.6%
5 381184
11.5%
8 322689
9.8%
3 322209
9.7%
9 271258
8.2%
2 262807
7.9%
0 236187
7.1%
4 235135
7.1%
Uppercase Letter
ValueCountFrequency (%)
A 2
50.0%
T 1
25.0%
N 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 670205
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 569111
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4548430
> 99.9%
Latin 24
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 3
12.5%
a 3
12.5%
i 3
12.5%
A 2
 
8.3%
o 2
 
8.3%
c 2
 
8.3%
s 1
 
4.2%
T 1
 
4.2%
p 1
 
4.2%
l 1
 
4.2%
Other values (5) 5
20.8%
Common
ValueCountFrequency (%)
. 670205
14.7%
- 569111
12.5%
7 494921
10.9%
1 399449
8.8%
6 383274
8.4%
5 381184
8.4%
8 322689
7.1%
3 322209
7.1%
9 271258
6.0%
2 262807
 
5.8%
Other values (3) 471323
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4548454
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 670205
14.7%
- 569111
12.5%
7 494921
10.9%
1 399449
8.8%
6 383274
8.4%
5 381184
8.4%
8 322689
7.1%
3 322209
7.1%
9 271258
6.0%
2 262807
 
5.8%
Other values (18) 471347
10.4%

geodeticDatum
Text

Missing 

Distinct13
Distinct (%)< 0.1%
Missing4485859
Missing (%)99.3%
Memory size34.5 MiB
2025-01-14T11:45:36.432121image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length18
Mean length14.73068922
Min length4

Characters and Unicode

Total characters439004
Distinct characters31
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowWGS84
2nd rowWGS 84 (EPSG:4326)
3rd rowWGS84
4th rowWGS 84 (EPSG:4326)
5th rowWGS 84 (EPSG:4326)
ValueCountFrequency (%)
wgs 20853
28.3%
84 20853
28.3%
epsg:4326 20842
28.2%
wgs84 6659
 
9.0%
not 1679
 
2.3%
recorded 1679
 
2.3%
nad83 385
 
0.5%
epsg:4269 385
 
0.5%
epsg:4267 212
 
0.3%
nad27 212
 
0.3%
Other values (8) 24
 
< 0.1%
2025-01-14T11:45:36.554466image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 48970
11.2%
G 48969
11.2%
S 48960
11.2%
43981
10.0%
8 27912
 
6.4%
W 27512
 
6.3%
2 21661
 
4.9%
( 21448
 
4.9%
E 21448
 
4.9%
P 21448
 
4.9%
Other values (21) 106695
24.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 173319
39.5%
Decimal Number 142056
32.4%
Space Separator 43981
 
10.0%
Open Punctuation 21448
 
4.9%
Other Punctuation 21448
 
4.9%
Close Punctuation 21448
 
4.9%
Lowercase Letter 15299
 
3.5%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 48970
34.5%
8 27912
19.6%
2 21661
15.2%
6 21439
15.1%
3 21239
15.0%
7 425
 
0.3%
9 397
 
0.3%
1 9
 
< 0.1%
0 3
 
< 0.1%
5 1
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
G 48969
28.3%
S 48960
28.2%
W 27512
15.9%
E 21448
12.4%
P 21448
12.4%
N 2183
 
1.3%
R 1585
 
0.9%
A 607
 
0.4%
D 607
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
e 3358
21.9%
d 3358
21.9%
o 3358
21.9%
r 1773
11.6%
t 1679
11.0%
c 1679
11.0%
n 94
 
0.6%
Space Separator
ValueCountFrequency (%)
43981
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21448
100.0%
Other Punctuation
ValueCountFrequency (%)
: 21448
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21448
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 250386
57.0%
Latin 188618
43.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
G 48969
26.0%
S 48960
26.0%
W 27512
14.6%
E 21448
11.4%
P 21448
11.4%
e 3358
 
1.8%
d 3358
 
1.8%
o 3358
 
1.8%
N 2183
 
1.2%
r 1773
 
0.9%
Other values (6) 6251
 
3.3%
Common
ValueCountFrequency (%)
4 48970
19.6%
43981
17.6%
8 27912
11.1%
2 21661
8.7%
( 21448
8.6%
: 21448
8.6%
) 21448
8.6%
6 21439
8.6%
3 21239
8.5%
7 425
 
0.2%
Other values (5) 415
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 439004
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 48970
11.2%
G 48969
11.2%
S 48960
11.2%
43981
10.0%
8 27912
 
6.4%
W 27512
 
6.3%
2 21661
 
4.9%
( 21448
 
4.9%
E 21448
 
4.9%
P 21448
 
4.9%
Other values (21) 106695
24.3%

coordinateUncertaintyInMeters
Text

Missing 

Distinct21
Distinct (%)0.3%
Missing4509192
Missing (%)99.9%
Memory size34.5 MiB
2025-01-14T11:45:36.615675image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.866439944
Min length1

Characters and Unicode

Total characters25012
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row16000
2nd row1500
3rd row250
4th row500
5th row1500
ValueCountFrequency (%)
16000 1334
20.6%
1000 1304
20.2%
500 1065
16.5%
3000 624
9.6%
250 622
9.6%
750 305
 
4.7%
5000 282
 
4.4%
1500 267
 
4.1%
2000 202
 
3.1%
3500 148
 
2.3%
Other values (11) 316
 
4.9%
2025-01-14T11:45:36.738914image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15790
63.1%
1 3052
 
12.2%
5 2771
 
11.1%
6 1370
 
5.5%
2 879
 
3.5%
3 785
 
3.1%
7 305
 
1.2%
8 50
 
0.2%
4 10
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25012
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15790
63.1%
1 3052
 
12.2%
5 2771
 
11.1%
6 1370
 
5.5%
2 879
 
3.5%
3 785
 
3.1%
7 305
 
1.2%
8 50
 
0.2%
4 10
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 25012
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15790
63.1%
1 3052
 
12.2%
5 2771
 
11.1%
6 1370
 
5.5%
2 879
 
3.5%
3 785
 
3.1%
7 305
 
1.2%
8 50
 
0.2%
4 10
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25012
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15790
63.1%
1 3052
 
12.2%
5 2771
 
11.1%
6 1370
 
5.5%
2 879
 
3.5%
3 785
 
3.1%
7 305
 
1.2%
8 50
 
0.2%
4 10
 
< 0.1%

coordinatePrecision
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing4515658
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:36.788915image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row315
2nd row112
3rd row151
ValueCountFrequency (%)
315 1
33.3%
112 1
33.3%
151 1
33.3%
2025-01-14T11:45:36.888314image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
55.6%
5 2
 
22.2%
3 1
 
11.1%
2 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
55.6%
5 2
 
22.2%
3 1
 
11.1%
2 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Common 9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
55.6%
5 2
 
22.2%
3 1
 
11.1%
2 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
55.6%
5 2
 
22.2%
3 1
 
11.1%
2 1
 
11.1%

pointRadiusSpatialFit
Text

Missing 

Distinct5
Distinct (%)100.0%
Missing4515656
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:36.941875image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length3
Mean length6.2
Min length3

Characters and Unicode

Total characters31
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row315
2nd rowUnited States
3rd rowIndonesia
4th row112
5th row151
ValueCountFrequency (%)
315 1
16.7%
united 1
16.7%
states 1
16.7%
indonesia 1
16.7%
112 1
16.7%
151 1
16.7%
2025-01-14T11:45:37.047772image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
16.1%
n 3
9.7%
t 3
9.7%
e 3
9.7%
5 2
 
6.5%
i 2
 
6.5%
d 2
 
6.5%
a 2
 
6.5%
s 2
 
6.5%
3 1
 
3.2%
Other values (6) 6
19.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18
58.1%
Decimal Number 9
29.0%
Uppercase Letter 3
 
9.7%
Space Separator 1
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 3
16.7%
t 3
16.7%
e 3
16.7%
i 2
11.1%
d 2
11.1%
a 2
11.1%
s 2
11.1%
o 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 5
55.6%
5 2
 
22.2%
3 1
 
11.1%
2 1
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
U 1
33.3%
S 1
33.3%
I 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21
67.7%
Common 10
32.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 3
14.3%
t 3
14.3%
e 3
14.3%
i 2
9.5%
d 2
9.5%
a 2
9.5%
s 2
9.5%
U 1
 
4.8%
S 1
 
4.8%
I 1
 
4.8%
Common
ValueCountFrequency (%)
1 5
50.0%
5 2
 
20.0%
3 1
 
10.0%
1
 
10.0%
2 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
16.1%
n 3
9.7%
t 3
9.7%
e 3
9.7%
5 2
 
6.5%
i 2
 
6.5%
d 2
 
6.5%
a 2
 
6.5%
s 2
 
6.5%
3 1
 
3.2%
Other values (6) 6
19.4%

verbatimCoordinates
Text

Missing 

Distinct4
Distinct (%)100.0%
Missing4515657
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:37.095856image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters16
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row1938
2nd row1988
3rd row1883
4th row1907
ValueCountFrequency (%)
1938 1
25.0%
1988 1
25.0%
1883 1
25.0%
1907 1
25.0%
2025-01-14T11:45:37.192453image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 5
31.2%
1 4
25.0%
9 3
18.8%
3 2
 
12.5%
0 1
 
6.2%
7 1
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 5
31.2%
1 4
25.0%
9 3
18.8%
3 2
 
12.5%
0 1
 
6.2%
7 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 16
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 5
31.2%
1 4
25.0%
9 3
18.8%
3 2
 
12.5%
0 1
 
6.2%
7 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 5
31.2%
1 4
25.0%
9 3
18.8%
3 2
 
12.5%
0 1
 
6.2%
7 1
 
6.2%

verbatimLatitude
Text

Missing 

Distinct5653
Distinct (%)14.9%
Missing4477670
Missing (%)99.2%
Memory size34.5 MiB
2025-01-14T11:45:37.375434image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length66
Median length28
Mean length8.207575478
Min length1

Characters and Unicode

Total characters311814
Distinct characters58
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2975 ?
Unique (%)7.8%

Sample

1st row26 16'43"N
2nd row24 58.74' N
3rd row55 56'N
4th row24 47'31"N
5th row19.75856
ValueCountFrequency (%)
n 20751
23.6%
0 7933
 
9.0%
26 2620
 
3.0%
24 2619
 
3.0%
18 2373
 
2.7%
16 2094
 
2.4%
9 1686
 
1.9%
25 1666
 
1.9%
s 1527
 
1.7%
2.2228 1275
 
1.5%
Other values (4210) 43266
49.3%
2025-01-14T11:45:37.636304image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49819
16.0%
N 29862
9.6%
2 27458
8.8%
3 24694
 
7.9%
1 23158
 
7.4%
0 22687
 
7.3%
4 21103
 
6.8%
5 17039
 
5.5%
6 15718
 
5.0%
' 15536
 
5.0%
Other values (48) 64740
20.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 185765
59.6%
Space Separator 49819
 
16.0%
Other Punctuation 40475
 
13.0%
Uppercase Letter 32869
 
10.5%
Dash Punctuation 1489
 
0.5%
Lowercase Letter 1036
 
0.3%
Other Symbol 286
 
0.1%
Other Letter 60
 
< 0.1%
Math Symbol 15
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 166
16.0%
g 145
14.0%
d 135
13.0%
t 133
12.8%
a 91
8.8%
n 75
7.2%
r 50
 
4.8%
o 48
 
4.6%
i 46
 
4.4%
h 40
 
3.9%
Other values (9) 107
10.3%
Uppercase Letter
ValueCountFrequency (%)
N 29862
90.9%
S 2903
 
8.8%
L 71
 
0.2%
W 11
 
< 0.1%
E 5
 
< 0.1%
M 4
 
< 0.1%
T 4
 
< 0.1%
A 3
 
< 0.1%
X 2
 
< 0.1%
U 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 27458
14.8%
3 24694
13.3%
1 23158
12.5%
0 22687
12.2%
4 21103
11.4%
5 17039
9.2%
6 15718
8.5%
8 13067
7.0%
9 11407
6.1%
7 9434
 
5.1%
Other Punctuation
ValueCountFrequency (%)
' 15536
38.4%
. 14598
36.1%
" 9732
24.0%
; 450
 
1.1%
: 77
 
0.2%
, 42
 
0.1%
? 29
 
0.1%
/ 8
 
< 0.1%
′ 3
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
= 11
73.3%
~ 3
 
20.0%
+ 1
 
6.7%
Space Separator
ValueCountFrequency (%)
49819
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1489
100.0%
Other Symbol
ValueCountFrequency (%)
° 286
100.0%
Other Letter
ValueCountFrequency (%)
º 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 277849
89.1%
Latin 33965
 
10.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 29862
87.9%
S 2903
 
8.5%
e 166
 
0.5%
g 145
 
0.4%
d 135
 
0.4%
t 133
 
0.4%
a 91
 
0.3%
n 75
 
0.2%
L 71
 
0.2%
º 60
 
0.2%
Other values (23) 324
 
1.0%
Common
ValueCountFrequency (%)
49819
17.9%
2 27458
9.9%
3 24694
8.9%
1 23158
8.3%
0 22687
8.2%
4 21103
7.6%
5 17039
 
6.1%
6 15718
 
5.7%
' 15536
 
5.6%
. 14598
 
5.3%
Other values (15) 46039
16.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 311465
99.9%
None 346
 
0.1%
Punctuation 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49819
16.0%
N 29862
9.6%
2 27458
8.8%
3 24694
 
7.9%
1 23158
 
7.4%
0 22687
 
7.3%
4 21103
 
6.8%
5 17039
 
5.5%
6 15718
 
5.0%
' 15536
 
5.0%
Other values (45) 64391
20.7%
None
ValueCountFrequency (%)
° 286
82.7%
º 60
 
17.3%
Punctuation
ValueCountFrequency (%)
′ 3
100.0%

verbatimLongitude
Text

Missing 

Distinct5598
Distinct (%)14.7%
Missing4477686
Missing (%)99.2%
Memory size34.5 MiB
2025-01-14T11:45:37.830696image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length68
Median length29
Mean length8.566662278
Min length1

Characters and Unicode

Total characters325319
Distinct characters51
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2941 ?
Unique (%)7.7%

Sample

1st row83 46'49"W
2nd row76 12.75' W
3rd row11 55'E
4th row83 41'11"W
5th row-97.63925
ValueCountFrequency (%)
w 11522
 
13.1%
e 10550
 
12.0%
0 7784
 
8.8%
82 2500
 
2.8%
88 1824
 
2.1%
79 1618
 
1.8%
83 1559
 
1.8%
51 1335
 
1.5%
9.91722 1275
 
1.4%
48.5 1155
 
1.3%
Other values (4274) 46881
53.3%
2025-01-14T11:45:38.104845image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50028
15.4%
0 24928
 
7.7%
1 24695
 
7.6%
7 23700
 
7.3%
W 20627
 
6.3%
2 19465
 
6.0%
4 19360
 
6.0%
5 19032
 
5.9%
8 18801
 
5.8%
3 16059
 
4.9%
Other values (41) 88624
27.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195862
60.2%
Space Separator 50028
 
15.4%
Other Punctuation 41461
 
12.7%
Uppercase Letter 32895
 
10.1%
Dash Punctuation 3709
 
1.1%
Lowercase Letter 1034
 
0.3%
Other Symbol 270
 
0.1%
Other Letter 60
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
g 218
21.1%
e 187
18.1%
d 135
13.1%
n 118
11.4%
o 77
 
7.4%
s 63
 
6.1%
t 48
 
4.6%
i 47
 
4.5%
a 38
 
3.7%
w 35
 
3.4%
Other values (7) 68
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
W 20627
62.7%
E 11910
36.2%
O 142
 
0.4%
N 120
 
0.4%
L 84
 
0.3%
M 3
 
< 0.1%
T 3
 
< 0.1%
Y 2
 
< 0.1%
S 2
 
< 0.1%
Q 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 24928
12.7%
1 24695
12.6%
7 23700
12.1%
2 19465
9.9%
4 19360
9.9%
5 19032
9.7%
8 18801
9.6%
3 16059
8.2%
9 15402
7.9%
6 14420
7.4%
Other Punctuation
ValueCountFrequency (%)
. 15592
37.6%
' 15535
37.5%
" 9717
23.4%
; 498
 
1.2%
, 47
 
0.1%
: 28
 
0.1%
? 26
 
0.1%
/ 15
 
< 0.1%
′ 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
50028
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3709
100.0%
Other Symbol
ValueCountFrequency (%)
° 270
100.0%
Other Letter
ValueCountFrequency (%)
º 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 291330
89.6%
Latin 33989
 
10.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
W 20627
60.7%
E 11910
35.0%
g 218
 
0.6%
e 187
 
0.6%
O 142
 
0.4%
d 135
 
0.4%
N 120
 
0.4%
n 118
 
0.3%
L 84
 
0.2%
o 77
 
0.2%
Other values (19) 371
 
1.1%
Common
ValueCountFrequency (%)
50028
17.2%
0 24928
8.6%
1 24695
8.5%
7 23700
 
8.1%
2 19465
 
6.7%
4 19360
 
6.6%
5 19032
 
6.5%
8 18801
 
6.5%
3 16059
 
5.5%
. 15592
 
5.4%
Other values (12) 59670
20.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 324986
99.9%
None 330
 
0.1%
Punctuation 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50028
15.4%
0 24928
 
7.7%
1 24695
 
7.6%
7 23700
 
7.3%
W 20627
 
6.3%
2 19465
 
6.0%
4 19360
 
6.0%
5 19032
 
5.9%
8 18801
 
5.8%
3 16059
 
4.9%
Other values (38) 88291
27.2%
None
ValueCountFrequency (%)
° 270
81.8%
º 60
 
18.2%
Punctuation
ValueCountFrequency (%)
′ 3
100.0%

verbatimCoordinateSystem
Text

Missing 

Distinct6
Distinct (%)< 0.1%
Missing4478628
Missing (%)99.2%
Memory size34.5 MiB
2025-01-14T11:45:38.172329image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length23
Mean length22.98007183
Min length4

Characters and Unicode

Total characters851021
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowDegrees Minutes Seconds
2nd rowDegrees Minutes Seconds
3rd rowDegrees Minutes Seconds
4th rowDegrees Minutes Seconds
5th rowDegrees Minutes Seconds
ValueCountFrequency (%)
degrees 37003
33.3%
minutes 36978
33.3%
seconds 36978
33.3%
decimal 25
 
< 0.1%
quad 22
 
< 0.1%
unknown 6
 
< 0.1%
11 1
 
< 0.1%
nov 1
 
< 0.1%
1938 1
 
< 0.1%
21 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
2025-01-14T11:45:38.300495image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 184990
21.7%
s 110959
13.0%
73985
 
8.7%
n 73974
 
8.7%
D 37025
 
4.4%
r 37004
 
4.3%
i 37003
 
4.3%
c 37003
 
4.3%
d 37003
 
4.3%
g 37003
 
4.3%
Other values (21) 185072
21.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 665969
78.3%
Uppercase Letter 111055
 
13.0%
Space Separator 73985
 
8.7%
Decimal Number 12
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 184990
27.8%
s 110959
16.7%
n 73974
 
11.1%
r 37004
 
5.6%
i 37003
 
5.6%
c 37003
 
5.6%
d 37003
 
5.6%
g 37003
 
5.6%
o 36985
 
5.6%
u 36978
 
5.6%
Other values (8) 37067
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
D 37025
33.3%
M 36978
33.3%
S 36978
33.3%
U 28
 
< 0.1%
A 23
 
< 0.1%
Q 22
 
< 0.1%
N 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 5
41.7%
8 3
25.0%
9 2
 
16.7%
3 1
 
8.3%
2 1
 
8.3%
Space Separator
ValueCountFrequency (%)
73985
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 777024
91.3%
Common 73997
 
8.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 184990
23.8%
s 110959
14.3%
n 73974
 
9.5%
D 37025
 
4.8%
r 37004
 
4.8%
i 37003
 
4.8%
c 37003
 
4.8%
d 37003
 
4.8%
g 37003
 
4.8%
o 36985
 
4.8%
Other values (15) 148075
19.1%
Common
ValueCountFrequency (%)
73985
> 99.9%
1 5
 
< 0.1%
8 3
 
< 0.1%
9 2
 
< 0.1%
3 1
 
< 0.1%
2 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 851021
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 184990
21.7%
s 110959
13.0%
73985
 
8.7%
n 73974
 
8.7%
D 37025
 
4.4%
r 37004
 
4.3%
i 37003
 
4.3%
c 37003
 
4.3%
d 37003
 
4.3%
g 37003
 
4.3%
Other values (21) 185072
21.7%

verbatimSRS
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing4515660
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:38.352194image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters13
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowSan Francisco
ValueCountFrequency (%)
san 1
50.0%
francisco 1
50.0%
2025-01-14T11:45:38.453531image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2
15.4%
n 2
15.4%
c 2
15.4%
S 1
7.7%
1
7.7%
F 1
7.7%
r 1
7.7%
i 1
7.7%
s 1
7.7%
o 1
7.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10
76.9%
Uppercase Letter 2
 
15.4%
Space Separator 1
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2
20.0%
n 2
20.0%
c 2
20.0%
r 1
10.0%
i 1
10.0%
s 1
10.0%
o 1
10.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
F 1
50.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
92.3%
Common 1
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2
16.7%
n 2
16.7%
c 2
16.7%
S 1
8.3%
F 1
8.3%
r 1
8.3%
i 1
8.3%
s 1
8.3%
o 1
8.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2
15.4%
n 2
15.4%
c 2
15.4%
S 1
7.7%
1
7.7%
F 1
7.7%
r 1
7.7%
i 1
7.7%
s 1
7.7%
o 1
7.7%

footprintSpatialFit
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing4515658
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:38.516747image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length33
Median length19
Mean length23
Min length17

Characters and Unicode

Total characters69
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowAsplenium monanthes
2nd rowNymphoides indica
3rd rowKohleria inaequalis var. lindenii
ValueCountFrequency (%)
asplenium 1
12.5%
monanthes 1
12.5%
nymphoides 1
12.5%
indica 1
12.5%
kohleria 1
12.5%
inaequalis 1
12.5%
var 1
12.5%
lindenii 1
12.5%
2025-01-14T11:45:38.642725image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 10
14.5%
n 7
 
10.1%
a 6
 
8.7%
e 6
 
8.7%
5
 
7.2%
l 4
 
5.8%
s 4
 
5.8%
h 3
 
4.3%
o 3
 
4.3%
m 3
 
4.3%
Other values (13) 18
26.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 60
87.0%
Space Separator 5
 
7.2%
Uppercase Letter 3
 
4.3%
Other Punctuation 1
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 10
16.7%
n 7
11.7%
a 6
10.0%
e 6
10.0%
l 4
 
6.7%
s 4
 
6.7%
h 3
 
5.0%
o 3
 
5.0%
m 3
 
5.0%
d 3
 
5.0%
Other values (8) 11
18.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
A 1
33.3%
N 1
33.3%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 63
91.3%
Common 6
 
8.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 10
15.9%
n 7
11.1%
a 6
9.5%
e 6
9.5%
l 4
 
6.3%
s 4
 
6.3%
h 3
 
4.8%
o 3
 
4.8%
m 3
 
4.8%
d 3
 
4.8%
Other values (11) 14
22.2%
Common
ValueCountFrequency (%)
5
83.3%
. 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 10
14.5%
n 7
 
10.1%
a 6
 
8.7%
e 6
 
8.7%
5
 
7.2%
l 4
 
5.8%
s 4
 
5.8%
h 3
 
4.3%
o 3
 
4.3%
m 3
 
4.3%
Other values (13) 18
26.1%

georeferenceProtocol
Text

Missing 

Distinct20
Distinct (%)< 0.1%
Missing4388537
Missing (%)97.2%
Memory size34.5 MiB
2025-01-14T11:45:38.704214image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length16
Mean length8.340360593
Min length3

Characters and Unicode

Total characters1060260
Distinct characters40
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowGazetteer
2nd rowGazetteer
3rd rowGazetteer
4th rowGazetteer
5th rowLabel
ValueCountFrequency (%)
gazetteer 49173
29.7%
gps 23394
14.1%
gis 20969
12.7%
arcview 20969
12.7%
label 17064
 
10.3%
google 15524
 
9.4%
maps 12428
 
7.5%
earth 3096
 
1.9%
source 1688
 
1.0%
g-1 397
 
0.2%
Other values (11) 704
 
0.4%
2025-01-14T11:45:38.837365image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 203052
19.2%
G 109414
 
10.3%
t 101502
 
9.6%
a 82086
 
7.7%
r 74984
 
7.1%
z 49173
 
4.6%
S 45993
 
4.3%
38282
 
3.6%
o 32954
 
3.1%
l 32699
 
3.1%
Other values (30) 290121
27.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 728213
68.7%
Uppercase Letter 251029
 
23.7%
Space Separator 38282
 
3.6%
Close Punctuation 20969
 
2.0%
Open Punctuation 20969
 
2.0%
Dash Punctuation 397
 
< 0.1%
Decimal Number 397
 
< 0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 203052
27.9%
t 101502
13.9%
a 82086
11.3%
r 74984
 
10.3%
z 49173
 
6.8%
o 32954
 
4.5%
l 32699
 
4.5%
c 22672
 
3.1%
i 21073
 
2.9%
w 20981
 
2.9%
Other values (12) 87037
12.0%
Uppercase Letter
ValueCountFrequency (%)
G 109414
43.6%
S 45993
18.3%
P 23336
 
9.3%
I 20969
 
8.4%
A 20969
 
8.4%
L 17057
 
6.8%
M 9952
 
4.0%
E 3096
 
1.2%
W 176
 
0.1%
C 55
 
< 0.1%
Other values (2) 12
 
< 0.1%
Space Separator
ValueCountFrequency (%)
38282
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20969
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20969
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 397
100.0%
Decimal Number
ValueCountFrequency (%)
1 397
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 979242
92.4%
Common 81018
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 203052
20.7%
G 109414
11.2%
t 101502
10.4%
a 82086
 
8.4%
r 74984
 
7.7%
z 49173
 
5.0%
S 45993
 
4.7%
o 32954
 
3.4%
l 32699
 
3.3%
P 23336
 
2.4%
Other values (24) 224049
22.9%
Common
ValueCountFrequency (%)
38282
47.3%
) 20969
25.9%
( 20969
25.9%
- 397
 
0.5%
1 397
 
0.5%
. 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1060260
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 203052
19.2%
G 109414
 
10.3%
t 101502
 
9.6%
a 82086
 
7.7%
r 74984
 
7.1%
z 49173
 
4.6%
S 45993
 
4.3%
38282
 
3.6%
o 32954
 
3.1%
l 32699
 
3.1%
Other values (30) 290121
27.4%

georeferenceRemarks
Text

Missing 

Distinct78
Distinct (%)15.3%
Missing4515150
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:38.954543image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length67
Median length57
Mean length19.70254403
Min length1

Characters and Unicode

Total characters10068
Distinct characters64
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)5.7%

Sample

1st row+-1000m
2nd rowstop 1 - beginning of bike path, along GW pkwy
3rd rowca.; ca.
4th rowstop 1-ditch; stop 2- polkweed; stop 3; stop 4
5th rowLong. 4 8 W - 4 15 W
ValueCountFrequency (%)
stop 226
 
10.5%
4 144
 
6.7%
119
 
5.5%
w 106
 
4.9%
ca 90
 
4.2%
1 86
 
4.0%
seconds 56
 
2.6%
long 53
 
2.5%
15 53
 
2.5%
8 53
 
2.5%
Other values (116) 1167
54.2%
2025-01-14T11:45:39.149488image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1642
16.3%
o 738
 
7.3%
t 614
 
6.1%
e 593
 
5.9%
a 549
 
5.5%
n 536
 
5.3%
i 494
 
4.9%
s 437
 
4.3%
p 406
 
4.0%
l 382
 
3.8%
Other values (54) 3677
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6599
65.5%
Space Separator 1642
 
16.3%
Uppercase Letter 653
 
6.5%
Decimal Number 614
 
6.1%
Other Punctuation 341
 
3.4%
Dash Punctuation 195
 
1.9%
Math Symbol 20
 
0.2%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 738
11.2%
t 614
9.3%
e 593
9.0%
a 549
 
8.3%
n 536
 
8.1%
i 494
 
7.5%
s 437
 
6.6%
p 406
 
6.2%
l 382
 
5.8%
d 372
 
5.6%
Other values (14) 1478
22.4%
Uppercase Letter
ValueCountFrequency (%)
W 143
21.9%
S 113
17.3%
L 91
13.9%
G 47
 
7.2%
A 36
 
5.5%
F 28
 
4.3%
M 28
 
4.3%
T 28
 
4.3%
C 26
 
4.0%
U 25
 
3.8%
Other values (9) 88
13.5%
Decimal Number
ValueCountFrequency (%)
1 197
32.1%
4 156
25.4%
8 64
 
10.4%
5 58
 
9.4%
0 53
 
8.6%
2 42
 
6.8%
3 40
 
6.5%
6 3
 
0.5%
7 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 205
60.1%
; 90
26.4%
, 33
 
9.7%
/ 10
 
2.9%
: 2
 
0.6%
' 1
 
0.3%
Math Symbol
ValueCountFrequency (%)
+ 17
85.0%
± 3
 
15.0%
Space Separator
ValueCountFrequency (%)
1642
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 195
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7252
72.0%
Common 2816
 
28.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 738
 
10.2%
t 614
 
8.5%
e 593
 
8.2%
a 549
 
7.6%
n 536
 
7.4%
i 494
 
6.8%
s 437
 
6.0%
p 406
 
5.6%
l 382
 
5.3%
d 372
 
5.1%
Other values (33) 2131
29.4%
Common
ValueCountFrequency (%)
1642
58.3%
. 205
 
7.3%
1 197
 
7.0%
- 195
 
6.9%
4 156
 
5.5%
; 90
 
3.2%
8 64
 
2.3%
5 58
 
2.1%
0 53
 
1.9%
2 42
 
1.5%
Other values (11) 114
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10065
> 99.9%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1642
16.3%
o 738
 
7.3%
t 614
 
6.1%
e 593
 
5.9%
a 549
 
5.5%
n 536
 
5.3%
i 494
 
4.9%
s 437
 
4.3%
p 406
 
4.0%
l 382
 
3.8%
Other values (53) 3674
36.5%
None
ValueCountFrequency (%)
± 3
100.0%

geologicalContextID
Text

Missing 

Distinct4
Distinct (%)100.0%
Missing4515657
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:39.218583image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length56
Median length49
Mean length49
Min length42

Characters and Unicode

Total characters196
Distinct characters30
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowSouth America - Neotropics, Colombia, Meta
2nd rowSouth America - Neotropics, Ecuador, Morona-Santiago
3rd rowNorth America, United States, California, San Bernardino
4th rowNorth America, United States, Arizona, Cochise
ValueCountFrequency (%)
america 4
16.0%
south 2
 
8.0%
2
 
8.0%
neotropics 2
 
8.0%
north 2
 
8.0%
united 2
 
8.0%
states 2
 
8.0%
colombia 1
 
4.0%
meta 1
 
4.0%
ecuador 1
 
4.0%
Other values (6) 6
24.0%
2025-01-14T11:45:39.354829image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
10.7%
o 18
 
9.2%
a 17
 
8.7%
i 15
 
7.7%
t 14
 
7.1%
r 14
 
7.1%
e 13
 
6.6%
, 10
 
5.1%
n 9
 
4.6%
c 8
 
4.1%
Other values (20) 57
29.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 138
70.4%
Uppercase Letter 24
 
12.2%
Space Separator 21
 
10.7%
Other Punctuation 10
 
5.1%
Dash Punctuation 3
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 18
13.0%
a 17
12.3%
i 15
10.9%
t 14
10.1%
r 14
10.1%
e 13
9.4%
n 9
6.5%
c 8
 
5.8%
m 5
 
3.6%
h 5
 
3.6%
Other values (9) 20
14.5%
Uppercase Letter
ValueCountFrequency (%)
S 6
25.0%
A 5
20.8%
N 4
16.7%
C 3
12.5%
U 2
 
8.3%
M 2
 
8.3%
E 1
 
4.2%
B 1
 
4.2%
Space Separator
ValueCountFrequency (%)
21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 162
82.7%
Common 34
 
17.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 18
11.1%
a 17
 
10.5%
i 15
 
9.3%
t 14
 
8.6%
r 14
 
8.6%
e 13
 
8.0%
n 9
 
5.6%
c 8
 
4.9%
S 6
 
3.7%
m 5
 
3.1%
Other values (17) 43
26.5%
Common
ValueCountFrequency (%)
21
61.8%
, 10
29.4%
- 3
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 196
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
 
10.7%
o 18
 
9.2%
a 17
 
8.7%
i 15
 
7.7%
t 14
 
7.1%
r 14
 
7.1%
e 13
 
6.6%
, 10
 
5.1%
n 9
 
4.6%
c 8
 
4.1%
Other values (20) 57
29.1%

earliestEonOrLowestEonothem
Text

Missing 

Distinct5
Distinct (%)71.4%
Missing4515654
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:39.425869image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length49
Median length48
Mean length31.57142857
Min length13

Characters and Unicode

Total characters221
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)42.9%

Sample

1st rowSouth America - Neotropics
2nd rowPlantae, Pteridophyte, Polypodiales, Aspleniaceae
3rd rowPlantae, Dicotyledonae, Asterales, Menyanthaceae
4th rowPlantae, Dicotyledonae, Lamiales, Gesneriaceae
5th rowSouth America - Neotropics
ValueCountFrequency (%)
america 4
16.7%
plantae 3
12.5%
south 2
8.3%
2
8.3%
neotropics 2
8.3%
north 2
8.3%
dicotyledonae 2
8.3%
pteridophyte 1
 
4.2%
polypodiales 1
 
4.2%
aspleniaceae 1
 
4.2%
Other values (4) 4
16.7%
2025-01-14T11:45:39.560670image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 29
13.1%
a 23
 
10.4%
17
 
7.7%
o 15
 
6.8%
t 15
 
6.8%
i 13
 
5.9%
c 11
 
5.0%
r 11
 
5.0%
l 10
 
4.5%
, 9
 
4.1%
Other values (17) 68
30.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 171
77.4%
Uppercase Letter 22
 
10.0%
Space Separator 17
 
7.7%
Other Punctuation 9
 
4.1%
Dash Punctuation 2
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 29
17.0%
a 23
13.5%
o 15
8.8%
t 15
8.8%
i 13
7.6%
c 11
 
6.4%
r 11
 
6.4%
l 10
 
5.8%
n 9
 
5.3%
s 8
 
4.7%
Other values (6) 27
15.8%
Uppercase Letter
ValueCountFrequency (%)
A 6
27.3%
P 5
22.7%
N 4
18.2%
D 2
 
9.1%
S 2
 
9.1%
M 1
 
4.5%
L 1
 
4.5%
G 1
 
4.5%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 193
87.3%
Common 28
 
12.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 29
15.0%
a 23
11.9%
o 15
 
7.8%
t 15
 
7.8%
i 13
 
6.7%
c 11
 
5.7%
r 11
 
5.7%
l 10
 
5.2%
n 9
 
4.7%
s 8
 
4.1%
Other values (14) 49
25.4%
Common
ValueCountFrequency (%)
17
60.7%
, 9
32.1%
- 2
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 221
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 29
13.1%
a 23
 
10.4%
17
 
7.7%
o 15
 
6.8%
t 15
 
6.8%
i 13
 
5.9%
c 11
 
5.0%
r 11
 
5.0%
l 10
 
4.5%
, 9
 
4.1%
Other values (17) 68
30.8%

latestEonOrHighestEonothem
Text

Missing 

Distinct5
Distinct (%)71.4%
Missing4515654
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:39.622002image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length27
Median length13
Mean length12.14285714
Min length7

Characters and Unicode

Total characters85
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)57.1%

Sample

1st rowAlgae name updating Project
2nd rowEarle, S. A.
3rd rowPlantae
4th rowPlantae
5th rowBlair, S. M.
ValueCountFrequency (%)
plantae 3
18.8%
s 2
12.5%
algae 1
 
6.2%
name 1
 
6.2%
updating 1
 
6.2%
project 1
 
6.2%
earle 1
 
6.2%
a 1
 
6.2%
blair 1
 
6.2%
m 1
 
6.2%
Other values (3) 3
18.8%
2025-01-14T11:45:39.750091image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 11
12.9%
9
 
10.6%
e 8
 
9.4%
n 7
 
8.2%
l 6
 
7.1%
. 6
 
7.1%
t 5
 
5.9%
P 4
 
4.7%
, 3
 
3.5%
r 3
 
3.5%
Other values (17) 23
27.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 53
62.4%
Uppercase Letter 14
 
16.5%
Space Separator 9
 
10.6%
Other Punctuation 9
 
10.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 11
20.8%
e 8
15.1%
n 7
13.2%
l 6
11.3%
t 5
9.4%
r 3
 
5.7%
i 3
 
5.7%
g 2
 
3.8%
p 1
 
1.9%
d 1
 
1.9%
Other values (6) 6
11.3%
Uppercase Letter
ValueCountFrequency (%)
P 4
28.6%
S 2
14.3%
A 2
14.3%
D 2
14.3%
E 1
 
7.1%
B 1
 
7.1%
M 1
 
7.1%
G 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 6
66.7%
, 3
33.3%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 67
78.8%
Common 18
 
21.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 11
16.4%
e 8
11.9%
n 7
10.4%
l 6
 
9.0%
t 5
 
7.5%
P 4
 
6.0%
r 3
 
4.5%
i 3
 
4.5%
g 2
 
3.0%
S 2
 
3.0%
Other values (14) 16
23.9%
Common
ValueCountFrequency (%)
9
50.0%
. 6
33.3%
, 3
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 11
12.9%
9
 
10.6%
e 8
 
9.4%
n 7
 
8.2%
l 6
 
7.1%
. 6
 
7.1%
t 5
 
5.9%
P 4
 
4.7%
, 3
 
3.5%
r 3
 
3.5%
Other values (17) 23
27.1%

latestEraOrHighestErathem
Text

Missing 

Distinct2
Distinct (%)66.7%
Missing4515658
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:39.804617image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.66666667
Min length12

Characters and Unicode

Total characters38
Distinct characters15
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowPteridophyte
2nd rowDicotyledonae
3rd rowDicotyledonae
ValueCountFrequency (%)
dicotyledonae 2
66.7%
pteridophyte 1
33.3%
2025-01-14T11:45:39.915969image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 6
15.8%
o 5
13.2%
t 4
10.5%
i 3
7.9%
y 3
7.9%
d 3
7.9%
D 2
 
5.3%
c 2
 
5.3%
l 2
 
5.3%
n 2
 
5.3%
Other values (5) 6
15.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 35
92.1%
Uppercase Letter 3
 
7.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6
17.1%
o 5
14.3%
t 4
11.4%
i 3
8.6%
y 3
8.6%
d 3
8.6%
c 2
 
5.7%
l 2
 
5.7%
n 2
 
5.7%
a 2
 
5.7%
Other values (3) 3
8.6%
Uppercase Letter
ValueCountFrequency (%)
D 2
66.7%
P 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 38
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6
15.8%
o 5
13.2%
t 4
10.5%
i 3
7.9%
y 3
7.9%
d 3
7.9%
D 2
 
5.3%
c 2
 
5.3%
l 2
 
5.3%
n 2
 
5.3%
Other values (5) 6
15.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 6
15.8%
o 5
13.2%
t 4
10.5%
i 3
7.9%
y 3
7.9%
d 3
7.9%
D 2
 
5.3%
c 2
 
5.3%
l 2
 
5.3%
n 2
 
5.3%
Other values (5) 6
15.8%

earliestPeriodOrLowestSystem
Text

Missing 

Distinct6
Distinct (%)85.7%
Missing4515654
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:39.972881image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10
Min length7

Characters and Unicode

Total characters70
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)71.4%

Sample

1st rowColombia
2nd rowPolypodiales
3rd rowAsterales
4th rowLamiales
5th rowEcuador
ValueCountFrequency (%)
united 2
22.2%
states 2
22.2%
colombia 1
11.1%
polypodiales 1
11.1%
asterales 1
11.1%
lamiales 1
11.1%
ecuador 1
11.1%
2025-01-14T11:45:40.100591image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 8
11.4%
a 8
11.4%
t 7
 
10.0%
s 6
 
8.6%
l 5
 
7.1%
o 5
 
7.1%
i 5
 
7.1%
d 4
 
5.7%
r 2
 
2.9%
m 2
 
2.9%
Other values (14) 18
25.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 59
84.3%
Uppercase Letter 9
 
12.9%
Space Separator 2
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8
13.6%
a 8
13.6%
t 7
11.9%
s 6
10.2%
l 5
8.5%
o 5
8.5%
i 5
8.5%
d 4
6.8%
r 2
 
3.4%
m 2
 
3.4%
Other values (6) 7
11.9%
Uppercase Letter
ValueCountFrequency (%)
U 2
22.2%
S 2
22.2%
C 1
11.1%
P 1
11.1%
A 1
11.1%
L 1
11.1%
E 1
11.1%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 68
97.1%
Common 2
 
2.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8
11.8%
a 8
11.8%
t 7
10.3%
s 6
 
8.8%
l 5
 
7.4%
o 5
 
7.4%
i 5
 
7.4%
d 4
 
5.9%
r 2
 
2.9%
m 2
 
2.9%
Other values (13) 16
23.5%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8
11.4%
a 8
11.4%
t 7
 
10.0%
s 6
 
8.6%
l 5
 
7.1%
o 5
 
7.1%
i 5
 
7.1%
d 4
 
5.7%
r 2
 
2.9%
m 2
 
2.9%
Other values (14) 18
25.7%

earliestEpochOrLowestSeries
Text

Missing 

Distinct7
Distinct (%)100.0%
Missing4515654
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:40.164248image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length12
Mean length10.42857143
Min length4

Characters and Unicode

Total characters73
Distinct characters22
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowMeta
2nd rowAspleniaceae
3rd rowMenyanthaceae
4th rowGesneriaceae
5th rowMorona-Santiago
ValueCountFrequency (%)
meta 1
14.3%
aspleniaceae 1
14.3%
menyanthaceae 1
14.3%
gesneriaceae 1
14.3%
morona-santiago 1
14.3%
california 1
14.3%
arizona 1
14.3%
2025-01-14T11:45:40.292443image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 14
19.2%
e 11
15.1%
n 8
11.0%
i 6
8.2%
o 5
 
6.8%
r 4
 
5.5%
M 3
 
4.1%
t 3
 
4.1%
c 3
 
4.1%
A 2
 
2.7%
Other values (12) 14
19.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 64
87.7%
Uppercase Letter 8
 
11.0%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 14
21.9%
e 11
17.2%
n 8
12.5%
i 6
9.4%
o 5
 
7.8%
r 4
 
6.2%
t 3
 
4.7%
c 3
 
4.7%
s 2
 
3.1%
l 2
 
3.1%
Other values (6) 6
9.4%
Uppercase Letter
ValueCountFrequency (%)
M 3
37.5%
A 2
25.0%
S 1
 
12.5%
C 1
 
12.5%
G 1
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 72
98.6%
Common 1
 
1.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 14
19.4%
e 11
15.3%
n 8
11.1%
i 6
8.3%
o 5
 
6.9%
r 4
 
5.6%
M 3
 
4.2%
t 3
 
4.2%
c 3
 
4.2%
A 2
 
2.8%
Other values (11) 13
18.1%
Common
ValueCountFrequency (%)
- 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 14
19.2%
e 11
15.1%
n 8
11.0%
i 6
8.2%
o 5
 
6.8%
r 4
 
5.5%
M 3
 
4.1%
t 3
 
4.1%
c 3
 
4.1%
A 2
 
2.7%
Other values (12) 14
19.2%

latestEpochOrHighestSeries
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing4515659
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:40.344251image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length10.5
Mean length10.5
Min length7

Characters and Unicode

Total characters21
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowSan Bernardino
2nd rowCochise
ValueCountFrequency (%)
san 1
33.3%
bernardino 1
33.3%
cochise 1
33.3%
2025-01-14T11:45:40.460811image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 3
14.3%
a 2
9.5%
e 2
9.5%
r 2
9.5%
i 2
9.5%
o 2
9.5%
S 1
 
4.8%
1
 
4.8%
B 1
 
4.8%
d 1
 
4.8%
Other values (4) 4
19.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17
81.0%
Uppercase Letter 3
 
14.3%
Space Separator 1
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 3
17.6%
a 2
11.8%
e 2
11.8%
r 2
11.8%
i 2
11.8%
o 2
11.8%
d 1
 
5.9%
c 1
 
5.9%
h 1
 
5.9%
s 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
B 1
33.3%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20
95.2%
Common 1
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 3
15.0%
a 2
10.0%
e 2
10.0%
r 2
10.0%
i 2
10.0%
o 2
10.0%
S 1
 
5.0%
B 1
 
5.0%
d 1
 
5.0%
C 1
 
5.0%
Other values (3) 3
15.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 3
14.3%
a 2
9.5%
e 2
9.5%
r 2
9.5%
i 2
9.5%
o 2
9.5%
S 1
 
4.8%
1
 
4.8%
B 1
 
4.8%
d 1
 
4.8%
Other values (4) 4
19.0%

latestAgeOrHighestStage
Text

Missing 

Distinct4
Distinct (%)100.0%
Missing4515657
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:40.540718image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length84
Median length46
Mean length47.75
Min length15

Characters and Unicode

Total characters191
Distinct characters37
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowVilla Vicencia.
2nd rowMorona-Santiago: Cordillera del Boliche; about 60 km from Limon south to Gualaquiza.
3rd rowSouthern California. Lugonia. San Berdo Co.
4th rowChiricahua Mountains, Barfoot Park, stony knolls.
ValueCountFrequency (%)
villa 1
 
3.8%
vicencia 1
 
3.8%
stony 1
 
3.8%
park 1
 
3.8%
barfoot 1
 
3.8%
mountains 1
 
3.8%
chiricahua 1
 
3.8%
co 1
 
3.8%
berdo 1
 
3.8%
san 1
 
3.8%
Other values (16) 16
61.5%
2025-01-14T11:45:40.688207image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22
 
11.5%
o 20
 
10.5%
a 19
 
9.9%
i 14
 
7.3%
n 12
 
6.3%
r 10
 
5.2%
l 10
 
5.2%
u 8
 
4.2%
t 8
 
4.2%
e 6
 
3.1%
Other values (27) 62
32.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 138
72.3%
Space Separator 22
 
11.5%
Uppercase Letter 18
 
9.4%
Other Punctuation 10
 
5.2%
Decimal Number 2
 
1.0%
Dash Punctuation 1
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 20
14.5%
a 19
13.8%
i 14
10.1%
n 12
8.7%
r 10
 
7.2%
l 10
 
7.2%
u 8
 
5.8%
t 8
 
5.8%
e 6
 
4.3%
h 5
 
3.6%
Other values (11) 26
18.8%
Uppercase Letter
ValueCountFrequency (%)
C 4
22.2%
B 3
16.7%
S 3
16.7%
L 2
11.1%
V 2
11.1%
M 2
11.1%
G 1
 
5.6%
P 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 6
60.0%
, 2
 
20.0%
; 1
 
10.0%
: 1
 
10.0%
Decimal Number
ValueCountFrequency (%)
6 1
50.0%
0 1
50.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 156
81.7%
Common 35
 
18.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 20
12.8%
a 19
12.2%
i 14
 
9.0%
n 12
 
7.7%
r 10
 
6.4%
l 10
 
6.4%
u 8
 
5.1%
t 8
 
5.1%
e 6
 
3.8%
h 5
 
3.2%
Other values (19) 44
28.2%
Common
ValueCountFrequency (%)
22
62.9%
. 6
 
17.1%
, 2
 
5.7%
6 1
 
2.9%
0 1
 
2.9%
; 1
 
2.9%
: 1
 
2.9%
- 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 191
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22
 
11.5%
o 20
 
10.5%
a 19
 
9.9%
i 14
 
7.3%
n 12
 
6.3%
r 10
 
5.2%
l 10
 
5.2%
u 8
 
4.2%
t 8
 
4.2%
e 6
 
3.1%
Other values (27) 62
32.5%

lowestBiostratigraphicZone
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing4515658
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:40.743248image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length9
Mean length9
Min length8

Characters and Unicode

Total characters27
Distinct characters17
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowAsplenium
2nd rowNymphoides
3rd rowKohleria
ValueCountFrequency (%)
asplenium 1
33.3%
nymphoides 1
33.3%
kohleria 1
33.3%
2025-01-14T11:45:40.860939image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3
11.1%
i 3
11.1%
m 2
 
7.4%
h 2
 
7.4%
p 2
 
7.4%
l 2
 
7.4%
s 2
 
7.4%
o 2
 
7.4%
r 1
 
3.7%
K 1
 
3.7%
Other values (7) 7
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
88.9%
Uppercase Letter 3
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3
12.5%
i 3
12.5%
m 2
8.3%
h 2
8.3%
p 2
8.3%
l 2
8.3%
s 2
8.3%
o 2
8.3%
r 1
 
4.2%
d 1
 
4.2%
Other values (4) 4
16.7%
Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
A 1
33.3%
N 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 27
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3
11.1%
i 3
11.1%
m 2
 
7.4%
h 2
 
7.4%
p 2
 
7.4%
l 2
 
7.4%
s 2
 
7.4%
o 2
 
7.4%
r 1
 
3.7%
K 1
 
3.7%
Other values (7) 7
25.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 3
11.1%
i 3
11.1%
m 2
 
7.4%
h 2
 
7.4%
p 2
 
7.4%
l 2
 
7.4%
s 2
 
7.4%
o 2
 
7.4%
r 1
 
3.7%
K 1
 
3.7%
Other values (7) 7
25.9%

highestBiostratigraphicZone
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing4515658
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:40.909896image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.666666667
Min length5

Characters and Unicode

Total characters17
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row500.0
2nd row1650.0
3rd row2438.0
ValueCountFrequency (%)
500.0 1
33.3%
1650.0 1
33.3%
2438.0 1
33.3%
2025-01-14T11:45:41.008579image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6
35.3%
. 3
17.6%
5 2
 
11.8%
1 1
 
5.9%
6 1
 
5.9%
2 1
 
5.9%
4 1
 
5.9%
3 1
 
5.9%
8 1
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
82.4%
Other Punctuation 3
 
17.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6
42.9%
5 2
 
14.3%
1 1
 
7.1%
6 1
 
7.1%
2 1
 
7.1%
4 1
 
7.1%
3 1
 
7.1%
8 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6
35.3%
. 3
17.6%
5 2
 
11.8%
1 1
 
5.9%
6 1
 
5.9%
2 1
 
5.9%
4 1
 
5.9%
3 1
 
5.9%
8 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6
35.3%
. 3
17.6%
5 2
 
11.8%
1 1
 
5.9%
6 1
 
5.9%
2 1
 
5.9%
4 1
 
5.9%
3 1
 
5.9%
8 1
 
5.9%

lithostratigraphicTerms
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing4515660
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:41.052892image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row500.0
ValueCountFrequency (%)
500.0 1
100.0%
2025-01-14T11:45:41.146688image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3
60.0%
5 1
 
20.0%
. 1
 
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
80.0%
Other Punctuation 1
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3
75.0%
5 1
 
25.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3
60.0%
5 1
 
20.0%
. 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3
60.0%
5 1
 
20.0%
. 1
 
20.0%

formation
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing4515658
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:41.194717image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.333333333
Min length6

Characters and Unicode

Total characters25
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowmonanthes
2nd rowindica
3rd rowinaequalis
ValueCountFrequency (%)
monanthes 1
33.3%
indica 1
33.3%
inaequalis 1
33.3%
2025-01-14T11:45:41.306226image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 4
16.0%
a 4
16.0%
i 4
16.0%
e 2
8.0%
s 2
8.0%
m 1
 
4.0%
o 1
 
4.0%
t 1
 
4.0%
h 1
 
4.0%
d 1
 
4.0%
Other values (4) 4
16.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 25
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 4
16.0%
a 4
16.0%
i 4
16.0%
e 2
8.0%
s 2
8.0%
m 1
 
4.0%
o 1
 
4.0%
t 1
 
4.0%
h 1
 
4.0%
d 1
 
4.0%
Other values (4) 4
16.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 25
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 4
16.0%
a 4
16.0%
i 4
16.0%
e 2
8.0%
s 2
8.0%
m 1
 
4.0%
o 1
 
4.0%
t 1
 
4.0%
h 1
 
4.0%
d 1
 
4.0%
Other values (4) 4
16.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 4
16.0%
a 4
16.0%
i 4
16.0%
e 2
8.0%
s 2
8.0%
m 1
 
4.0%
o 1
 
4.0%
t 1
 
4.0%
h 1
 
4.0%
d 1
 
4.0%
Other values (4) 4
16.0%

member
Text

Missing 

Distinct7
Distinct (%)100.0%
Missing4515654
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:41.369653image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length19
Mean length19.28571429
Min length8

Characters and Unicode

Total characters135
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowRinorea pubiflora var. pubiflora
2nd rowAgissea simulans
3rd rowColpomenia sinuosa
4th rowLaurencia intricata
5th rowAvrainvillea nigricans
ValueCountFrequency (%)
pubiflora 2
13.3%
rinorea 1
 
6.7%
var 1
 
6.7%
agissea 1
 
6.7%
simulans 1
 
6.7%
colpomenia 1
 
6.7%
sinuosa 1
 
6.7%
laurencia 1
 
6.7%
intricata 1
 
6.7%
avrainvillea 1
 
6.7%
Other values (4) 4
26.7%
2025-01-14T11:45:41.488776image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 20
14.8%
a 16
11.9%
n 14
10.4%
e 10
 
7.4%
s 8
 
5.9%
r 8
 
5.9%
8
 
5.9%
o 7
 
5.2%
l 7
 
5.2%
u 5
 
3.7%
Other values (16) 32
23.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 120
88.9%
Space Separator 8
 
5.9%
Uppercase Letter 6
 
4.4%
Other Punctuation 1
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 20
16.7%
a 16
13.3%
n 14
11.7%
e 10
8.3%
s 8
 
6.7%
r 8
 
6.7%
o 7
 
5.8%
l 7
 
5.8%
u 5
 
4.2%
m 4
 
3.3%
Other values (10) 21
17.5%
Uppercase Letter
ValueCountFrequency (%)
A 3
50.0%
R 1
 
16.7%
L 1
 
16.7%
C 1
 
16.7%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 126
93.3%
Common 9
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 20
15.9%
a 16
12.7%
n 14
11.1%
e 10
 
7.9%
s 8
 
6.3%
r 8
 
6.3%
o 7
 
5.6%
l 7
 
5.6%
u 5
 
4.0%
m 4
 
3.2%
Other values (14) 27
21.4%
Common
ValueCountFrequency (%)
8
88.9%
. 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 20
14.8%
a 16
11.9%
n 14
10.4%
e 10
 
7.4%
s 8
 
5.9%
r 8
 
5.9%
8
 
5.9%
o 7
 
5.2%
l 7
 
5.2%
u 5
 
3.7%
Other values (16) 32
23.7%

bed
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing4515660
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:41.541357image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters17
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowRiccardia pinguis
ValueCountFrequency (%)
riccardia 1
50.0%
pinguis 1
50.0%
2025-01-14T11:45:41.640064image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 4
23.5%
c 2
11.8%
a 2
11.8%
R 1
 
5.9%
r 1
 
5.9%
d 1
 
5.9%
1
 
5.9%
p 1
 
5.9%
n 1
 
5.9%
g 1
 
5.9%
Other values (2) 2
11.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15
88.2%
Uppercase Letter 1
 
5.9%
Space Separator 1
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 4
26.7%
c 2
13.3%
a 2
13.3%
r 1
 
6.7%
d 1
 
6.7%
p 1
 
6.7%
n 1
 
6.7%
g 1
 
6.7%
u 1
 
6.7%
s 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
R 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
94.1%
Common 1
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 4
25.0%
c 2
12.5%
a 2
12.5%
R 1
 
6.2%
r 1
 
6.2%
d 1
 
6.2%
p 1
 
6.2%
n 1
 
6.2%
g 1
 
6.2%
u 1
 
6.2%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 4
23.5%
c 2
11.8%
a 2
11.8%
R 1
 
5.9%
r 1
 
5.9%
d 1
 
5.9%
1
 
5.9%
p 1
 
5.9%
n 1
 
5.9%
g 1
 
5.9%
Other values (2) 2
11.8%

identificationID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing4515660
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:41.683510image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowVariety
ValueCountFrequency (%)
variety 1
100.0%
2025-01-14T11:45:41.778717image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
V 1
14.3%
a 1
14.3%
r 1
14.3%
i 1
14.3%
e 1
14.3%
t 1
14.3%
y 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6
85.7%
Uppercase Letter 1
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1
16.7%
r 1
16.7%
i 1
16.7%
e 1
16.7%
t 1
16.7%
y 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
V 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
V 1
14.3%
a 1
14.3%
r 1
14.3%
i 1
14.3%
e 1
14.3%
t 1
14.3%
y 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
V 1
14.3%
a 1
14.3%
r 1
14.3%
i 1
14.3%
e 1
14.3%
t 1
14.3%
y 1
14.3%

identificationQualifier
Text

Missing 

Distinct20
Distinct (%)0.2%
Missing4504655
Missing (%)99.8%
Memory size34.5 MiB
2025-01-14T11:45:41.832151image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length3
Mean length4.359985462
Min length2

Characters and Unicode

Total characters47986
Distinct characters29
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowcf.
2nd rowcf.
3rd rowcf.
4th rowvel aff.
5th rowvel aff.
ValueCountFrequency (%)
cf 5895
51.4%
aff 2849
24.9%
uncertain 1610
 
14.0%
s.l 543
 
4.7%
vel 347
 
3.0%
near 76
 
0.7%
sp 64
 
0.6%
nov 42
 
0.4%
s.s 27
 
0.2%
l 2
 
< 0.1%
Other values (7) 7
 
0.1%
2025-01-14T11:45:41.943309image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
f 11593
24.2%
. 9933
20.7%
c 7505
15.6%
a 4536
 
9.5%
n 3340
 
7.0%
e 2034
 
4.2%
r 1686
 
3.5%
t 1613
 
3.4%
i 1611
 
3.4%
u 1601
 
3.3%
Other values (19) 2534
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 37572
78.3%
Other Punctuation 9934
 
20.7%
Space Separator 456
 
1.0%
Uppercase Letter 20
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
f 11593
30.9%
c 7505
20.0%
a 4536
 
12.1%
n 3340
 
8.9%
e 2034
 
5.4%
r 1686
 
4.5%
t 1613
 
4.3%
i 1611
 
4.3%
u 1601
 
4.3%
l 890
 
2.4%
Other values (7) 1163
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
U 10
50.0%
L 4
 
20.0%
K 2
 
10.0%
H 1
 
5.0%
P 1
 
5.0%
E 1
 
5.0%
S 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 9933
> 99.9%
& 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
456
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 37592
78.3%
Common 10394
 
21.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
f 11593
30.8%
c 7505
20.0%
a 4536
 
12.1%
n 3340
 
8.9%
e 2034
 
5.4%
r 1686
 
4.5%
t 1613
 
4.3%
i 1611
 
4.3%
u 1601
 
4.3%
l 890
 
2.4%
Other values (14) 1183
 
3.1%
Common
ValueCountFrequency (%)
. 9933
95.6%
456
 
4.4%
( 2
 
< 0.1%
) 2
 
< 0.1%
& 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47986
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
f 11593
24.2%
. 9933
20.7%
c 7505
15.6%
a 4536
 
9.5%
n 3340
 
7.0%
e 2034
 
4.2%
r 1686
 
3.5%
t 1613
 
3.4%
i 1611
 
3.4%
u 1601
 
3.3%
Other values (19) 2534
 
5.3%

typeStatus
Text

Missing 

Distinct192
Distinct (%)0.2%
Missing4399315
Missing (%)97.4%
Memory size34.5 MiB
2025-01-14T11:45:42.002433image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length60
Median length7
Mean length8.824067867
Min length4

Characters and Unicode

Total characters1026645
Distinct characters36
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)0.1%

Sample

1st rowIsotype
2nd rowIsotype
3rd rowHolotype
4th rowType Collection
5th rowType Collection
ValueCountFrequency (%)
isotype 61603
45.1%
holotype 19964
 
14.6%
type 16845
 
12.3%
collection 9779
 
7.2%
isosyntype 7051
 
5.2%
syntype 6301
 
4.6%
fragment 5516
 
4.0%
isolectotype 2869
 
2.1%
possible 2534
 
1.9%
lectotype 1378
 
1.0%
Other values (16) 2653
 
1.9%
2025-01-14T11:45:42.144393image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 141371
13.8%
o 139676
13.6%
y 131094
12.8%
t 121736
11.9%
p 117820
11.5%
s 84712
8.3%
I 71992
7.0%
l 46312
 
4.5%
n 29146
 
2.8%
20147
 
2.0%
Other values (26) 122639
11.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 868423
84.6%
Uppercase Letter 136492
 
13.3%
Space Separator 20147
 
2.0%
Other Punctuation 1581
 
0.2%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 141371
16.3%
o 139676
16.1%
y 131094
15.1%
t 121736
14.0%
p 117820
13.6%
s 84712
9.8%
l 46312
 
5.3%
n 29146
 
3.4%
c 14142
 
1.6%
i 13202
 
1.5%
Other values (9) 29212
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
I 71992
52.7%
H 19964
 
14.6%
T 16846
 
12.3%
C 10393
 
7.6%
S 6301
 
4.6%
F 5516
 
4.0%
P 2922
 
2.1%
L 1378
 
1.0%
M 703
 
0.5%
N 275
 
0.2%
Other values (3) 202
 
0.1%
Space Separator
ValueCountFrequency (%)
20147
100.0%
Other Punctuation
ValueCountFrequency (%)
; 1581
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1004915
97.9%
Common 21730
 
2.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 141371
14.1%
o 139676
13.9%
y 131094
13.0%
t 121736
12.1%
p 117820
11.7%
s 84712
8.4%
I 71992
7.2%
l 46312
 
4.6%
n 29146
 
2.9%
H 19964
 
2.0%
Other values (22) 101092
10.1%
Common
ValueCountFrequency (%)
20147
92.7%
; 1581
 
7.3%
( 1
 
< 0.1%
) 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1026645
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 141371
13.8%
o 139676
13.6%
y 131094
12.8%
t 121736
11.9%
p 117820
11.5%
s 84712
8.3%
I 71992
7.0%
l 46312
 
4.5%
n 29146
 
2.8%
20147
 
2.0%
Other values (26) 122639
11.9%

identifiedBy
Text

Missing 

Distinct8134
Distinct (%)1.5%
Missing3958097
Missing (%)87.7%
Memory size34.5 MiB
2025-01-14T11:45:42.347226image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length131
Median length109
Mean length37.72206957
Min length2

Characters and Unicode

Total characters21032468
Distinct characters98
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2641 ?
Unique (%)0.5%

Sample

1st rowBlair, S. M.
2nd rowAcevedo-Rodríguez, P., (BOT), Smithsonian Institution - National Museum of Natural History (UNITED STATES)
3rd rowAcevedo-Rodríguez, P., (BOT), Smithsonian Institution - National Museum of Natural History (UNITED STATES)
4th rowWagner, W. L., (BOT), Smithsonian Institution - National Museum of Natural History (UNITED STATES)
5th rowWagner, W. L., (BOT), Smithsonian Institution - National Museum of Natural History (UNITED STATES)
ValueCountFrequency (%)
united 136541
 
4.2%
states 136495
 
4.2%
of 126287
 
3.8%
123596
 
3.8%
national 120671
 
3.7%
museum 119573
 
3.6%
smithsonian 118957
 
3.6%
natural 118768
 
3.6%
history 118661
 
3.6%
institution 118645
 
3.6%
Other values (6317) 2046516
62.3%
2025-01-14T11:45:42.632637image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2727146
 
13.0%
t 1181664
 
5.6%
a 1144451
 
5.4%
o 1117247
 
5.3%
i 1047010
 
5.0%
n 1030069
 
4.9%
, 907900
 
4.3%
. 858290
 
4.1%
r 853980
 
4.1%
e 836095
 
4.0%
Other values (88) 9328616
44.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10959399
52.1%
Uppercase Letter 4749667
22.6%
Space Separator 2727146
 
13.0%
Other Punctuation 1794634
 
8.5%
Open Punctuation 323090
 
1.5%
Close Punctuation 323090
 
1.5%
Dash Punctuation 155421
 
0.7%
Decimal Number 20
 
< 0.1%
Currency Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1181664
10.8%
a 1144451
10.4%
o 1117247
10.2%
i 1047010
9.6%
n 1030069
9.4%
r 853980
7.8%
e 836095
7.6%
u 685477
 
6.3%
s 684648
 
6.2%
l 499617
 
4.6%
Other values (36) 1879141
17.1%
Uppercase Letter
ValueCountFrequency (%)
S 615333
13.0%
T 580486
12.2%
N 453167
 
9.5%
E 392588
 
8.3%
I 286588
 
6.0%
A 283630
 
6.0%
M 267816
 
5.6%
D 257036
 
5.4%
U 221269
 
4.7%
H 211199
 
4.4%
Other values (21) 1180555
24.9%
Other Punctuation
ValueCountFrequency (%)
, 907900
50.6%
. 858290
47.8%
; 26380
 
1.5%
" 1134
 
0.1%
' 677
 
< 0.1%
& 187
 
< 0.1%
¡ 40
 
< 0.1%
/ 17
 
< 0.1%
? 8
 
< 0.1%
… 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 8
40.0%
0 6
30.0%
9 4
20.0%
1 2
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 320857
99.3%
[ 2233
 
0.7%
Close Punctuation
ValueCountFrequency (%)
) 320857
99.3%
] 2233
 
0.7%
Space Separator
ValueCountFrequency (%)
2727146
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 155421
100.0%
Currency Symbol
ValueCountFrequency (%)
¢ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15709066
74.7%
Common 5323402
 
25.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1181664
 
7.5%
a 1144451
 
7.3%
o 1117247
 
7.1%
i 1047010
 
6.7%
n 1030069
 
6.6%
r 853980
 
5.4%
e 836095
 
5.3%
u 685477
 
4.4%
s 684648
 
4.4%
S 615333
 
3.9%
Other values (67) 6513092
41.5%
Common
ValueCountFrequency (%)
2727146
51.2%
, 907900
 
17.1%
. 858290
 
16.1%
( 320857
 
6.0%
) 320857
 
6.0%
- 155421
 
2.9%
; 26380
 
0.5%
[ 2233
 
< 0.1%
] 2233
 
< 0.1%
" 1134
 
< 0.1%
Other values (11) 951
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21000075
99.8%
None 32392
 
0.2%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2727146
 
13.0%
t 1181664
 
5.6%
a 1144451
 
5.4%
o 1117247
 
5.3%
i 1047010
 
5.0%
n 1030069
 
4.9%
, 907900
 
4.3%
. 858290
 
4.1%
r 853980
 
4.1%
e 836095
 
4.0%
Other values (60) 9296223
44.3%
None
ValueCountFrequency (%)
í 18313
56.5%
á 3710
 
11.5%
é 3312
 
10.2%
ö 1488
 
4.6%
ñ 1400
 
4.3%
ü 1088
 
3.4%
ó 994
 
3.1%
ä 828
 
2.6%
ú 332
 
1.0%
ã 297
 
0.9%
Other values (17) 630
 
1.9%
Punctuation
ValueCountFrequency (%)
… 1
100.0%

identifiedByID
Text

Missing 

Distinct6
Distinct (%)100.0%
Missing4515655
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:42.716415image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length71
Median length65.5
Mean length65.5
Min length59

Characters and Unicode

Total characters393
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowPlantae, Dicotyledonae, Malpighiales, Violaceae, Violoideae
2nd rowPlantae, Rhodophyta, Florideophyceae, Peyssonneliales, Peyssonneliaceae
3rd rowChromista, Ochrophyta, Phaeophyceae, Ectocarpales, Scytosiphonaceae
4th rowPlantae, Rhodophyta, Florideophyceae, Ceramiales, Rhodomelaceae
5th rowPlantae, Chlorophyta, Ulvophyceae, Bryopsidales, Dichotomosiphonaceae
ValueCountFrequency (%)
plantae 5
16.7%
rhodophyta 2
 
6.7%
florideophyceae 2
 
6.7%
ulvophyceae 2
 
6.7%
chlorophyta 2
 
6.7%
ectocarpales 1
 
3.3%
cladophorales 1
 
3.3%
dichotomosiphonaceae 1
 
3.3%
bryopsidales 1
 
3.3%
rhodomelaceae 1
 
3.3%
Other values (12) 12
40.0%
2025-01-14T11:45:42.852825image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 47
12.0%
e 47
12.0%
o 37
 
9.4%
l 25
 
6.4%
, 24
 
6.1%
24
 
6.1%
h 23
 
5.9%
c 17
 
4.3%
i 16
 
4.1%
y 16
 
4.1%
Other values (22) 117
29.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 315
80.2%
Uppercase Letter 30
 
7.6%
Other Punctuation 24
 
6.1%
Space Separator 24
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 47
14.9%
e 47
14.9%
o 37
11.7%
l 25
7.9%
h 23
7.3%
c 17
 
5.4%
i 16
 
5.1%
y 16
 
5.1%
p 16
 
5.1%
t 15
 
4.8%
Other values (7) 56
17.8%
Uppercase Letter
ValueCountFrequency (%)
P 8
26.7%
C 5
16.7%
R 3
 
10.0%
V 2
 
6.7%
F 2
 
6.7%
D 2
 
6.7%
U 2
 
6.7%
B 1
 
3.3%
S 1
 
3.3%
E 1
 
3.3%
Other values (3) 3
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%
Space Separator
ValueCountFrequency (%)
24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 345
87.8%
Common 48
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 47
13.6%
e 47
13.6%
o 37
10.7%
l 25
 
7.2%
h 23
 
6.7%
c 17
 
4.9%
i 16
 
4.6%
y 16
 
4.6%
p 16
 
4.6%
t 15
 
4.3%
Other values (20) 86
24.9%
Common
ValueCountFrequency (%)
, 24
50.0%
24
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 393
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 47
12.0%
e 47
12.0%
o 37
 
9.4%
l 25
 
6.4%
, 24
 
6.1%
24
 
6.1%
h 23
 
5.9%
c 17
 
4.3%
i 16
 
4.1%
y 16
 
4.1%
Other values (22) 117
29.8%

dateIdentified
Text

Missing 

Distinct3
Distinct (%)42.9%
Missing4515654
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:42.915973image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length69
Median length7
Mean length16.14285714
Min length7

Characters and Unicode

Total characters113
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)28.6%

Sample

1st rowPlantae
2nd rowPlantae
3rd rowChromista
4th rowPlantae
5th rowPlantae
ValueCountFrequency (%)
plantae 6
54.5%
chromista 1
 
9.1%
marchantiophyta 1
 
9.1%
jungermanniopsida 1
 
9.1%
metzgeriales 1
 
9.1%
aneuraceae 1
 
9.1%
2025-01-14T11:45:43.033785image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 21
18.6%
e 13
11.5%
n 11
9.7%
t 10
 
8.8%
l 7
 
6.2%
P 6
 
5.3%
i 5
 
4.4%
r 5
 
4.4%
4
 
3.5%
, 4
 
3.5%
Other values (15) 27
23.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 94
83.2%
Uppercase Letter 11
 
9.7%
Space Separator 4
 
3.5%
Other Punctuation 4
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 21
22.3%
e 13
13.8%
n 11
11.7%
t 10
10.6%
l 7
 
7.4%
i 5
 
5.3%
r 5
 
5.3%
s 3
 
3.2%
o 3
 
3.2%
h 3
 
3.2%
Other values (8) 13
13.8%
Uppercase Letter
ValueCountFrequency (%)
P 6
54.5%
M 2
 
18.2%
C 1
 
9.1%
J 1
 
9.1%
A 1
 
9.1%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 105
92.9%
Common 8
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 21
20.0%
e 13
12.4%
n 11
10.5%
t 10
9.5%
l 7
 
6.7%
P 6
 
5.7%
i 5
 
4.8%
r 5
 
4.8%
s 3
 
2.9%
o 3
 
2.9%
Other values (13) 21
20.0%
Common
ValueCountFrequency (%)
4
50.0%
, 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 113
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 21
18.6%
e 13
11.5%
n 11
9.7%
t 10
 
8.8%
l 7
 
6.2%
P 6
 
5.3%
i 5
 
4.4%
r 5
 
4.4%
4
 
3.5%
, 4
 
3.5%
Other values (15) 27
23.9%

identificationReferences
Text

Missing 

Distinct4
Distinct (%)66.7%
Missing4515655
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:43.091525image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length10.5
Mean length9.833333333
Min length7

Characters and Unicode

Total characters59
Distinct characters16
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st rowRhodophyta
2nd rowOchrophyta
3rd rowRhodophyta
4th rowChlorophyta
5th rowChlorophyta
ValueCountFrequency (%)
rhodophyta 2
33.3%
chlorophyta 2
33.3%
ochrophyta 1
16.7%
plantae 1
16.7%
2025-01-14T11:45:43.210399image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
h 10
16.9%
o 9
15.3%
a 7
11.9%
t 6
10.2%
p 5
8.5%
y 5
8.5%
l 3
 
5.1%
r 3
 
5.1%
R 2
 
3.4%
d 2
 
3.4%
Other values (6) 7
11.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 53
89.8%
Uppercase Letter 6
 
10.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
h 10
18.9%
o 9
17.0%
a 7
13.2%
t 6
11.3%
p 5
9.4%
y 5
9.4%
l 3
 
5.7%
r 3
 
5.7%
d 2
 
3.8%
c 1
 
1.9%
Other values (2) 2
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
R 2
33.3%
C 2
33.3%
O 1
16.7%
P 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 59
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
h 10
16.9%
o 9
15.3%
a 7
11.9%
t 6
10.2%
p 5
8.5%
y 5
8.5%
l 3
 
5.1%
r 3
 
5.1%
R 2
 
3.4%
d 2
 
3.4%
Other values (6) 7
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
h 10
16.9%
o 9
15.3%
a 7
11.9%
t 6
10.2%
p 5
8.5%
y 5
8.5%
l 3
 
5.1%
r 3
 
5.1%
R 2
 
3.4%
d 2
 
3.4%
Other values (6) 7
11.9%

identificationVerificationStatus
Text

Missing 

Distinct5
Distinct (%)71.4%
Missing4515654
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:43.268414image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length13
Mean length13.14285714
Min length11

Characters and Unicode

Total characters92
Distinct characters19
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)42.9%

Sample

1st rowDicotyledonae
2nd rowFlorideophyceae
3rd rowPhaeophyceae
4th rowFlorideophyceae
5th rowUlvophyceae
ValueCountFrequency (%)
florideophyceae 2
28.6%
ulvophyceae 2
28.6%
dicotyledonae 1
14.3%
phaeophyceae 1
14.3%
marchantiophyta 1
14.3%
2025-01-14T11:45:43.393883image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 15
16.3%
o 10
10.9%
a 10
10.9%
h 8
8.7%
y 7
7.6%
c 7
7.6%
p 6
 
6.5%
l 5
 
5.4%
i 4
 
4.3%
t 3
 
3.3%
Other values (9) 17
18.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 85
92.4%
Uppercase Letter 7
 
7.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 15
17.6%
o 10
11.8%
a 10
11.8%
h 8
9.4%
y 7
8.2%
c 7
8.2%
p 6
 
7.1%
l 5
 
5.9%
i 4
 
4.7%
t 3
 
3.5%
Other values (4) 10
11.8%
Uppercase Letter
ValueCountFrequency (%)
F 2
28.6%
U 2
28.6%
D 1
14.3%
P 1
14.3%
M 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 92
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 15
16.3%
o 10
10.9%
a 10
10.9%
h 8
8.7%
y 7
7.6%
c 7
7.6%
p 6
 
6.5%
l 5
 
5.4%
i 4
 
4.3%
t 3
 
3.3%
Other values (9) 17
18.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 15
16.3%
o 10
10.9%
a 10
10.9%
h 8
8.7%
y 7
7.6%
c 7
7.6%
p 6
 
6.5%
l 5
 
5.4%
i 4
 
4.3%
t 3
 
3.3%
Other values (9) 17
18.5%

identificationRemarks
Text

Missing 

Distinct7
Distinct (%)100.0%
Missing4515654
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:43.456705image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length15
Mean length13
Min length10

Characters and Unicode

Total characters91
Distinct characters23
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowMalpighiales
2nd rowPeyssonneliales
3rd rowEctocarpales
4th rowCeramiales
5th rowBryopsidales
ValueCountFrequency (%)
malpighiales 1
14.3%
peyssonneliales 1
14.3%
ectocarpales 1
14.3%
ceramiales 1
14.3%
bryopsidales 1
14.3%
cladophorales 1
14.3%
jungermanniopsida 1
14.3%
2025-01-14T11:45:43.592961image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 12
13.2%
e 10
11.0%
s 10
11.0%
l 9
9.9%
i 7
 
7.7%
o 6
 
6.6%
p 5
 
5.5%
r 5
 
5.5%
n 5
 
5.5%
d 3
 
3.3%
Other values (13) 19
20.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 84
92.3%
Uppercase Letter 7
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 12
14.3%
e 10
11.9%
s 10
11.9%
l 9
10.7%
i 7
8.3%
o 6
7.1%
p 5
6.0%
r 5
6.0%
n 5
6.0%
d 3
 
3.6%
Other values (7) 12
14.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
28.6%
B 1
14.3%
J 1
14.3%
M 1
14.3%
E 1
14.3%
P 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 91
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 12
13.2%
e 10
11.0%
s 10
11.0%
l 9
9.9%
i 7
 
7.7%
o 6
 
6.6%
p 5
 
5.5%
r 5
 
5.5%
n 5
 
5.5%
d 3
 
3.3%
Other values (13) 19
20.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 91
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 12
13.2%
e 10
11.0%
s 10
11.0%
l 9
9.9%
i 7
 
7.7%
o 6
 
6.6%
p 5
 
5.5%
r 5
 
5.5%
n 5
 
5.5%
d 3
 
3.3%
Other values (13) 19
20.9%

taxonID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing4515660
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:43.646758image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowMetzgeriales
ValueCountFrequency (%)
metzgeriales 1
100.0%
2025-01-14T11:45:43.755764image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3
25.0%
M 1
 
8.3%
t 1
 
8.3%
z 1
 
8.3%
g 1
 
8.3%
r 1
 
8.3%
i 1
 
8.3%
a 1
 
8.3%
l 1
 
8.3%
s 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11
91.7%
Uppercase Letter 1
 
8.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3
27.3%
t 1
 
9.1%
z 1
 
9.1%
g 1
 
9.1%
r 1
 
9.1%
i 1
 
9.1%
a 1
 
9.1%
l 1
 
9.1%
s 1
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
M 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3
25.0%
M 1
 
8.3%
t 1
 
8.3%
z 1
 
8.3%
g 1
 
8.3%
r 1
 
8.3%
i 1
 
8.3%
a 1
 
8.3%
l 1
 
8.3%
s 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 3
25.0%
M 1
 
8.3%
t 1
 
8.3%
z 1
 
8.3%
g 1
 
8.3%
r 1
 
8.3%
i 1
 
8.3%
a 1
 
8.3%
l 1
 
8.3%
s 1
 
8.3%

scientificNameID
Text

Missing 

Distinct6
Distinct (%)100.0%
Missing4515655
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:43.811941image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length15
Mean length14.66666667
Min length9

Characters and Unicode

Total characters88
Distinct characters20
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowViolaceae
2nd rowPeyssonneliaceae
3rd rowScytosiphonaceae
4th rowRhodomelaceae
5th rowDichotomosiphonaceae
ValueCountFrequency (%)
violaceae 1
16.7%
peyssonneliaceae 1
16.7%
scytosiphonaceae 1
16.7%
rhodomelaceae 1
16.7%
dichotomosiphonaceae 1
16.7%
anadyomenaceae 1
16.7%
2025-01-14T11:45:43.931973image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 16
18.2%
a 13
14.8%
o 11
12.5%
c 8
9.1%
n 6
 
6.8%
i 5
 
5.7%
s 4
 
4.5%
h 4
 
4.5%
l 3
 
3.4%
y 3
 
3.4%
Other values (10) 15
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 82
93.2%
Uppercase Letter 6
 
6.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 16
19.5%
a 13
15.9%
o 11
13.4%
c 8
9.8%
n 6
 
7.3%
i 5
 
6.1%
s 4
 
4.9%
h 4
 
4.9%
l 3
 
3.7%
y 3
 
3.7%
Other values (4) 9
11.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
16.7%
V 1
16.7%
R 1
16.7%
S 1
16.7%
P 1
16.7%
A 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 88
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 16
18.2%
a 13
14.8%
o 11
12.5%
c 8
9.1%
n 6
 
6.8%
i 5
 
5.7%
s 4
 
4.5%
h 4
 
4.5%
l 3
 
3.4%
y 3
 
3.4%
Other values (10) 15
17.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 16
18.2%
a 13
14.8%
o 11
12.5%
c 8
9.1%
n 6
 
6.8%
i 5
 
5.7%
s 4
 
4.5%
h 4
 
4.5%
l 3
 
3.4%
y 3
 
3.4%
Other values (10) 15
17.0%

acceptedNameUsageID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing4515660
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:43.986958image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAneuraceae
ValueCountFrequency (%)
aneuraceae 1
100.0%
2025-01-14T11:45:44.090171image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3
30.0%
a 2
20.0%
A 1
 
10.0%
n 1
 
10.0%
u 1
 
10.0%
r 1
 
10.0%
c 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9
90.0%
Uppercase Letter 1
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3
33.3%
a 2
22.2%
n 1
 
11.1%
u 1
 
11.1%
r 1
 
11.1%
c 1
 
11.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3
30.0%
a 2
20.0%
A 1
 
10.0%
n 1
 
10.0%
u 1
 
10.0%
r 1
 
10.0%
c 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 3
30.0%
a 2
20.0%
A 1
 
10.0%
n 1
 
10.0%
u 1
 
10.0%
r 1
 
10.0%
c 1
 
10.0%

nameAccordingToID
Text

Missing 

Distinct6
Distinct (%)100.0%
Missing4515655
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:44.151762image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.166666667
Min length7

Characters and Unicode

Total characters55
Distinct characters20
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowRinorea
2nd rowAgissea
3rd rowColpomenia
4th rowLaurencia
5th rowAvrainvillea
ValueCountFrequency (%)
rinorea 1
16.7%
agissea 1
16.7%
colpomenia 1
16.7%
laurencia 1
16.7%
avrainvillea 1
16.7%
anadyomene 1
16.7%
2025-01-14T11:45:44.270765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 8
14.5%
e 7
12.7%
n 6
10.9%
i 6
10.9%
o 4
 
7.3%
r 3
 
5.5%
A 3
 
5.5%
l 3
 
5.5%
s 2
 
3.6%
v 2
 
3.6%
Other values (10) 11
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 49
89.1%
Uppercase Letter 6
 
10.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 8
16.3%
e 7
14.3%
n 6
12.2%
i 6
12.2%
o 4
8.2%
r 3
 
6.1%
l 3
 
6.1%
s 2
 
4.1%
v 2
 
4.1%
m 2
 
4.1%
Other values (6) 6
12.2%
Uppercase Letter
ValueCountFrequency (%)
A 3
50.0%
R 1
 
16.7%
C 1
 
16.7%
L 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 55
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 8
14.5%
e 7
12.7%
n 6
10.9%
i 6
10.9%
o 4
 
7.3%
r 3
 
5.5%
A 3
 
5.5%
l 3
 
5.5%
s 2
 
3.6%
v 2
 
3.6%
Other values (10) 11
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 8
14.5%
e 7
12.7%
n 6
10.9%
i 6
10.9%
o 4
 
7.3%
r 3
 
5.5%
A 3
 
5.5%
l 3
 
5.5%
s 2
 
3.6%
v 2
 
3.6%
Other values (10) 11
20.0%

namePublishedInID
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing4515660
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:44.324033image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowRiccardia
ValueCountFrequency (%)
riccardia 1
100.0%
2025-01-14T11:45:44.430156image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2
22.2%
c 2
22.2%
a 2
22.2%
R 1
11.1%
r 1
11.1%
d 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
88.9%
Uppercase Letter 1
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2
25.0%
c 2
25.0%
a 2
25.0%
r 1
12.5%
d 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
R 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2
22.2%
c 2
22.2%
a 2
22.2%
R 1
11.1%
r 1
11.1%
d 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 2
22.2%
c 2
22.2%
a 2
22.2%
R 1
11.1%
r 1
11.1%
d 1
11.1%

scientificName
Text

Distinct330689
Distinct (%)7.3%
Missing13722
Missing (%)0.3%
Memory size34.5 MiB
2025-01-14T11:45:44.688535image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length136
Median length98
Mean length19.78998916
Min length5

Characters and Unicode

Total characters89093324
Distinct characters97
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121029 ?
Unique (%)2.7%

Sample

1st rowLithothamnion calcareum
2nd rowAmicia glandulosa
3rd rowTripogandra glandulosa
4th rowConnarus steyermarkii
5th rowTrichoneura grandiglumis
ValueCountFrequency (%)
sp 270265
 
2.8%
var 210171
 
2.2%
subsp 106168
 
1.1%
carex 58129
 
0.6%
indet 41306
 
0.4%
poa 30191
 
0.3%
cyperus 27842
 
0.3%
cladonia 27025
 
0.3%
paspalum 26142
 
0.3%
solanum 24852
 
0.3%
Other values (98717) 8921619
91.6%
2025-01-14T11:45:45.036083image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 10712057
 
12.0%
i 8471292
 
9.5%
e 5756840
 
6.5%
s 5576870
 
6.3%
r 5526161
 
6.2%
5241771
 
5.9%
o 5207769
 
5.8%
l 4893187
 
5.5%
n 4698467
 
5.3%
u 4559281
 
5.1%
Other values (87) 28449629
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 78580357
88.2%
Space Separator 5241771
 
5.9%
Uppercase Letter 4541706
 
5.1%
Other Punctuation 688084
 
0.8%
Dash Punctuation 21295
 
< 0.1%
Decimal Number 7089
 
< 0.1%
Open Punctuation 6499
 
< 0.1%
Close Punctuation 6499
 
< 0.1%
Math Symbol 24
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 10712057
13.6%
i 8471292
10.8%
e 5756840
 
7.3%
s 5576870
 
7.1%
r 5526161
 
7.0%
o 5207769
 
6.6%
l 4893187
 
6.2%
n 4698467
 
6.0%
u 4559281
 
5.8%
t 3890322
 
5.0%
Other values (29) 19288111
24.5%
Uppercase Letter
ValueCountFrequency (%)
C 644736
14.2%
P 590845
13.0%
S 445961
9.8%
A 406199
 
8.9%
M 289296
 
6.4%
L 244144
 
5.4%
E 239459
 
5.3%
D 213054
 
4.7%
B 194553
 
4.3%
H 183912
 
4.0%
Other values (19) 1089547
24.0%
Other Punctuation
ValueCountFrequency (%)
. 675591
98.2%
, 5059
 
0.7%
' 4244
 
0.6%
& 2296
 
0.3%
? 530
 
0.1%
" 206
 
< 0.1%
/ 145
 
< 0.1%
# 11
 
< 0.1%
§ 1
 
< 0.1%
* 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 2215
31.2%
0 1692
23.9%
1 1572
22.2%
5 1049
14.8%
9 142
 
2.0%
3 125
 
1.8%
7 110
 
1.6%
8 103
 
1.5%
6 52
 
0.7%
4 29
 
0.4%
Math Symbol
ValueCountFrequency (%)
× 20
83.3%
~ 3
 
12.5%
+ 1
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 6483
99.8%
[ 16
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 6483
99.8%
] 16
 
0.2%
Space Separator
ValueCountFrequency (%)
5241771
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21295
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 83122063
93.3%
Common 5971261
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 10712057
12.9%
i 8471292
 
10.2%
e 5756840
 
6.9%
s 5576870
 
6.7%
r 5526161
 
6.6%
o 5207769
 
6.3%
l 4893187
 
5.9%
n 4698467
 
5.7%
u 4559281
 
5.5%
t 3890322
 
4.7%
Other values (58) 23829817
28.7%
Common
ValueCountFrequency (%)
5241771
87.8%
. 675591
 
11.3%
- 21295
 
0.4%
( 6483
 
0.1%
) 6483
 
0.1%
, 5059
 
0.1%
' 4244
 
0.1%
& 2296
 
< 0.1%
2 2215
 
< 0.1%
0 1692
 
< 0.1%
Other values (19) 4132
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89092107
> 99.9%
None 1217
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 10712057
 
12.0%
i 8471292
 
9.5%
e 5756840
 
6.5%
s 5576870
 
6.3%
r 5526161
 
6.2%
5241771
 
5.9%
o 5207769
 
5.8%
l 4893187
 
5.5%
n 4698467
 
5.3%
u 4559281
 
5.1%
Other values (69) 28448412
31.9%
None
ValueCountFrequency (%)
ë 762
62.6%
á 110
 
9.0%
ö 107
 
8.8%
ü 88
 
7.2%
Á 45
 
3.7%
é 39
 
3.2%
ó 26
 
2.1%
× 20
 
1.6%
É 9
 
0.7%
Ø 3
 
0.2%
Other values (8) 8
 
0.7%

acceptedNameUsage
Text

Missing 

Distinct6
Distinct (%)100.0%
Missing4515655
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:45.107863image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.5
Min length7

Characters and Unicode

Total characters51
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowpubiflora
2nd rowsimulans
3rd rowsinuosa
4th rowintricata
5th rownigricans
ValueCountFrequency (%)
pubiflora 1
16.7%
simulans 1
16.7%
sinuosa 1
16.7%
intricata 1
16.7%
nigricans 1
16.7%
menziesii 1
16.7%
2025-01-14T11:45:45.234442image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 10
19.6%
a 6
11.8%
s 6
11.8%
n 6
11.8%
r 3
 
5.9%
u 3
 
5.9%
c 2
 
3.9%
e 2
 
3.9%
l 2
 
3.9%
o 2
 
3.9%
Other values (7) 9
17.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 51
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 10
19.6%
a 6
11.8%
s 6
11.8%
n 6
11.8%
r 3
 
5.9%
u 3
 
5.9%
c 2
 
3.9%
e 2
 
3.9%
l 2
 
3.9%
o 2
 
3.9%
Other values (7) 9
17.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 51
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 10
19.6%
a 6
11.8%
s 6
11.8%
n 6
11.8%
r 3
 
5.9%
u 3
 
5.9%
c 2
 
3.9%
e 2
 
3.9%
l 2
 
3.9%
o 2
 
3.9%
Other values (7) 9
17.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 10
19.6%
a 6
11.8%
s 6
11.8%
n 6
11.8%
r 3
 
5.9%
u 3
 
5.9%
c 2
 
3.9%
e 2
 
3.9%
l 2
 
3.9%
o 2
 
3.9%
Other values (7) 9
17.6%

parentNameUsage
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing4515659
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:45.289903image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length8
Mean length8
Min length7

Characters and Unicode

Total characters16
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowpubiflora
2nd rowpinguis
ValueCountFrequency (%)
pubiflora 1
50.0%
pinguis 1
50.0%
2025-01-14T11:45:45.401875image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 3
18.8%
p 2
12.5%
u 2
12.5%
b 1
 
6.2%
f 1
 
6.2%
l 1
 
6.2%
o 1
 
6.2%
r 1
 
6.2%
a 1
 
6.2%
n 1
 
6.2%
Other values (2) 2
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 3
18.8%
p 2
12.5%
u 2
12.5%
b 1
 
6.2%
f 1
 
6.2%
l 1
 
6.2%
o 1
 
6.2%
r 1
 
6.2%
a 1
 
6.2%
n 1
 
6.2%
Other values (2) 2
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 3
18.8%
p 2
12.5%
u 2
12.5%
b 1
 
6.2%
f 1
 
6.2%
l 1
 
6.2%
o 1
 
6.2%
r 1
 
6.2%
a 1
 
6.2%
n 1
 
6.2%
Other values (2) 2
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 3
18.8%
p 2
12.5%
u 2
12.5%
b 1
 
6.2%
f 1
 
6.2%
l 1
 
6.2%
o 1
 
6.2%
r 1
 
6.2%
a 1
 
6.2%
n 1
 
6.2%
Other values (2) 2
12.5%

nameAccordingTo
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing4515660
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:45.446200image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowvariety
ValueCountFrequency (%)
variety 1
100.0%
2025-01-14T11:45:45.541161image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
v 1
14.3%
a 1
14.3%
r 1
14.3%
i 1
14.3%
e 1
14.3%
t 1
14.3%
y 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
v 1
14.3%
a 1
14.3%
r 1
14.3%
i 1
14.3%
e 1
14.3%
t 1
14.3%
y 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 7
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
v 1
14.3%
a 1
14.3%
r 1
14.3%
i 1
14.3%
e 1
14.3%
t 1
14.3%
y 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
v 1
14.3%
a 1
14.3%
r 1
14.3%
i 1
14.3%
e 1
14.3%
t 1
14.3%
y 1
14.3%

namePublishedInYear
Text

Missing 

Distinct5
Distinct (%)100.0%
Missing4515656
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:45.603472image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length34
Median length27
Mean length21.6
Min length6

Characters and Unicode

Total characters108
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row(Benth.) Sprague & Sandwith
2nd row(Weber Bosse) Pestana et al.
3rd row(K. Mert. ex Roth) Derbes & Solier
4th rowJ.V.Lamouroux
5th rowDecne.
ValueCountFrequency (%)
2
 
11.1%
benth 1
 
5.6%
k 1
 
5.6%
j.v.lamouroux 1
 
5.6%
solier 1
 
5.6%
derbes 1
 
5.6%
roth 1
 
5.6%
ex 1
 
5.6%
mert 1
 
5.6%
al 1
 
5.6%
Other values (7) 7
38.9%
2025-01-14T11:45:45.727644image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 14
 
13.0%
13
 
12.0%
. 7
 
6.5%
t 6
 
5.6%
r 6
 
5.6%
a 6
 
5.6%
o 5
 
4.6%
n 4
 
3.7%
s 4
 
3.7%
( 3
 
2.8%
Other values (25) 40
37.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 65
60.2%
Uppercase Letter 15
 
13.9%
Space Separator 13
 
12.0%
Other Punctuation 9
 
8.3%
Open Punctuation 3
 
2.8%
Close Punctuation 3
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 14
21.5%
t 6
9.2%
r 6
9.2%
a 6
9.2%
o 5
 
7.7%
n 4
 
6.2%
s 4
 
6.2%
h 3
 
4.6%
u 3
 
4.6%
i 2
 
3.1%
Other values (9) 12
18.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
20.0%
B 2
13.3%
D 2
13.3%
L 1
 
6.7%
J 1
 
6.7%
V 1
 
6.7%
R 1
 
6.7%
M 1
 
6.7%
K 1
 
6.7%
P 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 7
77.8%
& 2
 
22.2%
Space Separator
ValueCountFrequency (%)
13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 80
74.1%
Common 28
 
25.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 14
17.5%
t 6
 
7.5%
r 6
 
7.5%
a 6
 
7.5%
o 5
 
6.2%
n 4
 
5.0%
s 4
 
5.0%
h 3
 
3.8%
S 3
 
3.8%
u 3
 
3.8%
Other values (20) 26
32.5%
Common
ValueCountFrequency (%)
13
46.4%
. 7
25.0%
( 3
 
10.7%
) 3
 
10.7%
& 2
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 14
 
13.0%
13
 
12.0%
. 7
 
6.5%
t 6
 
5.6%
r 6
 
5.6%
a 6
 
5.6%
o 5
 
4.6%
n 4
 
3.7%
s 4
 
3.7%
( 3
 
2.8%
Other values (25) 40
37.0%

higherClassification
Text

Distinct2220
Distinct (%)< 0.1%
Missing13879
Missing (%)0.3%
Memory size34.5 MiB
2025-01-14T11:45:45.898272image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length135
Median length89
Mean length55.77126436
Min length6

Characters and Unicode

Total characters251070074
Distinct characters60
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique232 ?
Unique (%)< 0.1%

Sample

1st rowPlantae, Rhodophyta, Corallinales, Lithothamniaceae
2nd rowPlantae, Dicotyledonae, Fabales, Fabaceae, Papilionoideae
3rd rowPlantae, Monocotyledonae, Commelinales, Commelinaceae
4th rowPlantae, Dicotyledonae, Oxalidales, Connaraceae
5th rowPlantae, Monocotyledonae, Poales, Poaceae, Chloridoideae
ValueCountFrequency (%)
plantae 4143724
 
19.6%
dicotyledonae 2583518
 
12.2%
monocotyledonae 909034
 
4.3%
poales 702157
 
3.3%
poaceae 502389
 
2.4%
asterales 380254
 
1.8%
asteraceae 358301
 
1.7%
asteroideae 282993
 
1.3%
pteridophyte 276624
 
1.3%
lamiales 266378
 
1.3%
Other values (2232) 10769135
50.9%
2025-01-14T11:45:46.157695image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 35371989
14.1%
e 35160991
14.0%
o 18857025
 
7.5%
16672725
 
6.6%
, 16563118
 
6.6%
l 16272824
 
6.5%
n 12770502
 
5.1%
t 12542392
 
5.0%
i 12457371
 
5.0%
c 11339619
 
4.5%
Other values (50) 63061518
25.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 196578462
78.3%
Uppercase Letter 21064893
 
8.4%
Space Separator 16672725
 
6.6%
Other Punctuation 16583195
 
6.6%
Close Punctuation 85296
 
< 0.1%
Open Punctuation 85296
 
< 0.1%
Dash Punctuation 207
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 35371989
18.0%
e 35160991
17.9%
o 18857025
9.6%
l 16272824
8.3%
n 12770502
 
6.5%
t 12542392
 
6.4%
i 12457371
 
6.3%
c 11339619
 
5.8%
s 7950561
 
4.0%
d 7948035
 
4.0%
Other values (17) 25907153
13.2%
Uppercase Letter
ValueCountFrequency (%)
P 7116979
33.8%
D 2790296
 
13.2%
A 1980335
 
9.4%
M 1829877
 
8.7%
C 1526896
 
7.2%
L 903009
 
4.3%
F 880493
 
4.2%
R 765320
 
3.6%
B 726846
 
3.5%
S 642548
 
3.1%
Other values (16) 1902294
 
9.0%
Other Punctuation
ValueCountFrequency (%)
, 16563118
99.9%
. 20069
 
0.1%
? 8
 
< 0.1%
Space Separator
ValueCountFrequency (%)
16672725
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85296
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85296
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 207
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 217643355
86.7%
Common 33426719
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 35371989
16.3%
e 35160991
16.2%
o 18857025
8.7%
l 16272824
 
7.5%
n 12770502
 
5.9%
t 12542392
 
5.8%
i 12457371
 
5.7%
c 11339619
 
5.2%
s 7950561
 
3.7%
d 7948035
 
3.7%
Other values (43) 46972046
21.6%
Common
ValueCountFrequency (%)
16672725
49.9%
, 16563118
49.6%
) 85296
 
0.3%
( 85296
 
0.3%
. 20069
 
0.1%
- 207
 
< 0.1%
? 8
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 251069452
> 99.9%
None 622
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 35371989
14.1%
e 35160991
14.0%
o 18857025
 
7.5%
16672725
 
6.6%
, 16563118
 
6.6%
l 16272824
 
6.5%
n 12770502
 
5.1%
t 12542392
 
5.0%
i 12457371
 
5.0%
c 11339619
 
4.5%
Other values (49) 63060896
25.1%
None
ValueCountFrequency (%)
ö 622
100.0%

kingdom
Text

Distinct13
Distinct (%)< 0.1%
Missing15585
Missing (%)0.3%
Memory size34.5 MiB
2025-01-14T11:45:46.222933image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length33
Median length7
Mean length6.96302618
Min length5

Characters and Unicode

Total characters31334147
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowPlantae
2nd rowPlantae
3rd rowPlantae
4th rowPlantae
5th rowPlantae
ValueCountFrequency (%)
plantae 4143685
92.1%
fungi 223269
 
5.0%
eubacteria 52558
 
1.2%
chromista 41845
 
0.9%
protista 38689
 
0.9%
protozoa 24
 
< 0.1%
incertae 3
 
< 0.1%
sedis 3
 
< 0.1%
prokaryota 2
 
< 0.1%
kingdom 2
 
< 0.1%
Other values (4) 4
 
< 0.1%
2025-01-14T11:45:46.331625image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 8473056
27.0%
n 4366962
13.9%
t 4315498
13.8%
e 4196255
13.4%
P 4182397
13.3%
l 4143685
13.2%
i 356370
 
1.1%
u 275829
 
0.9%
g 223272
 
0.7%
F 223267
 
0.7%
Other values (18) 577556
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26834068
85.6%
Uppercase Letter 4500071
 
14.4%
Space Separator 8
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 8473056
31.6%
n 4366962
16.3%
t 4315498
16.1%
e 4196255
15.6%
l 4143685
15.4%
i 356370
 
1.3%
u 275829
 
1.0%
g 223272
 
0.8%
r 133125
 
0.5%
o 80614
 
0.3%
Other values (11) 269402
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
P 4182397
92.9%
F 223267
 
5.0%
E 52559
 
1.2%
C 41845
 
0.9%
I 2
 
< 0.1%
B 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31334139
> 99.9%
Common 8
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 8473056
27.0%
n 4366962
13.9%
t 4315498
13.8%
e 4196255
13.4%
P 4182397
13.3%
l 4143685
13.2%
i 356370
 
1.1%
u 275829
 
0.9%
g 223272
 
0.7%
F 223267
 
0.7%
Other values (17) 577548
 
1.8%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31334147
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 8473056
27.0%
n 4366962
13.9%
t 4315498
13.8%
e 4196255
13.4%
P 4182397
13.3%
l 4143685
13.2%
i 356370
 
1.1%
u 275829
 
0.9%
g 223272
 
0.7%
F 223267
 
0.7%
Other values (18) 577556
 
1.8%

phylum
Text

Missing 

Distinct37
Distinct (%)< 0.1%
Missing3795307
Missing (%)84.0%
Memory size34.5 MiB
2025-01-14T11:45:46.397194image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length27
Median length10
Mean length10.45428498
Min length6

Characters and Unicode

Total characters7530786
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowRhodophyta
2nd rowBryophyta
3rd rowAscomycota
4th rowRhodophyta
5th rowBryophyta
ValueCountFrequency (%)
ascomycota 220381
30.6%
bryophyta 148369
20.6%
rhodophyta 121618
16.9%
cyanobacteria 52553
 
7.3%
chlorophyta 44629
 
6.2%
bacillariophyta 33225
 
4.6%
ochrophyta 29634
 
4.1%
marchantiophyta 26552
 
3.7%
pinophyta 21234
 
2.9%
miozoa 4849
 
0.7%
Other values (29) 18257
 
2.5%
2025-01-14T11:45:46.518176image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1114609
14.8%
a 950427
12.6%
y 866328
11.5%
t 747357
9.9%
h 664707
8.8%
c 586886
7.8%
p 438109
 
5.8%
r 348688
 
4.6%
s 224255
 
3.0%
m 222302
 
3.0%
Other values (26) 1367118
18.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6807890
90.4%
Uppercase Letter 720354
 
9.6%
Other Punctuation 1595
 
< 0.1%
Space Separator 947
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1114609
16.4%
a 950427
14.0%
y 866328
12.7%
t 747357
11.0%
h 664707
9.8%
c 586886
8.6%
p 438109
 
6.4%
r 348688
 
5.1%
s 224255
 
3.3%
m 222302
 
3.3%
Other values (11) 644222
9.5%
Uppercase Letter
ValueCountFrequency (%)
A 220877
30.7%
B 183494
25.5%
R 121618
16.9%
C 101098
14.0%
M 32077
 
4.5%
O 29634
 
4.1%
P 25420
 
3.5%
I 2540
 
0.4%
G 2063
 
0.3%
H 914
 
0.1%
Other values (3) 619
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 1595
100.0%
Space Separator
ValueCountFrequency (%)
947
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7528244
> 99.9%
Common 2542
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1114609
14.8%
a 950427
12.6%
y 866328
11.5%
t 747357
9.9%
h 664707
8.8%
c 586886
7.8%
p 438109
 
5.8%
r 348688
 
4.6%
s 224255
 
3.0%
m 222302
 
3.0%
Other values (24) 1364576
18.1%
Common
ValueCountFrequency (%)
. 1595
62.7%
947
37.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7530786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1114609
14.8%
a 950427
12.6%
y 866328
11.5%
t 747357
9.9%
h 664707
8.8%
c 586886
7.8%
p 438109
 
5.8%
r 348688
 
4.6%
s 224255
 
3.0%
m 222302
 
3.0%
Other values (26) 1367118
18.2%

class
Text

Missing 

Distinct88
Distinct (%)< 0.1%
Missing166450
Missing (%)3.7%
Memory size34.5 MiB
2025-01-14T11:45:46.586697image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length33
Median length13
Mean length13.51310502
Min length6

Characters and Unicode

Total characters58771345
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)< 0.1%

Sample

1st rowDicotyledonae
2nd rowMonocotyledonae
3rd rowDicotyledonae
4th rowMonocotyledonae
5th rowDicotyledonae
ValueCountFrequency (%)
dicotyledonae 2583517
58.2%
monocotyledonae 909034
 
20.5%
pteridophyte 276624
 
6.2%
lecanoromycetes 202991
 
4.6%
bryopsida 127668
 
2.9%
florideophyceae 89454
 
2.0%
basal 85188
 
1.9%
ulvophyceae 35522
 
0.8%
jungermanniopsida 25865
 
0.6%
pinopsida 23209
 
0.5%
Other values (80) 76533
 
1.7%
2025-01-14T11:45:46.719725image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 9980172
17.0%
e 8651381
14.7%
n 4733378
8.1%
t 4293923
7.3%
y 4289084
7.3%
a 4288463
7.3%
c 4090012
7.0%
d 4070361
6.9%
l 3713365
 
6.3%
i 3238121
 
5.5%
Other values (37) 7423085
12.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 54165150
92.2%
Uppercase Letter 4349208
 
7.4%
Space Separator 86394
 
0.1%
Open Punctuation 85188
 
0.1%
Close Punctuation 85188
 
0.1%
Other Punctuation 217
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 9980172
18.4%
e 8651381
16.0%
n 4733378
8.7%
t 4293923
7.9%
y 4289084
7.9%
a 4288463
7.9%
c 4090012
7.6%
d 4070361
7.5%
l 3713365
 
6.9%
i 3238121
 
6.0%
Other values (13) 2816890
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
D 2591725
59.6%
M 910509
 
20.9%
P 327909
 
7.5%
L 204284
 
4.7%
B 135509
 
3.1%
F 89454
 
2.1%
U 35524
 
0.8%
J 25865
 
0.6%
A 8728
 
0.2%
S 7620
 
0.2%
Other values (10) 12081
 
0.3%
Space Separator
ValueCountFrequency (%)
86394
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85188
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85188
100.0%
Other Punctuation
ValueCountFrequency (%)
. 217
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 58514358
99.6%
Common 256987
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 9980172
17.1%
e 8651381
14.8%
n 4733378
8.1%
t 4293923
7.3%
y 4289084
7.3%
a 4288463
7.3%
c 4090012
7.0%
d 4070361
7.0%
l 3713365
 
6.3%
i 3238121
 
5.5%
Other values (33) 7166098
12.2%
Common
ValueCountFrequency (%)
86394
33.6%
( 85188
33.1%
) 85188
33.1%
. 217
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58771345
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 9980172
17.0%
e 8651381
14.7%
n 4733378
8.1%
t 4293923
7.3%
y 4289084
7.3%
a 4288463
7.3%
c 4090012
7.0%
d 4070361
6.9%
l 3713365
 
6.3%
i 3238121
 
5.5%
Other values (37) 7423085
12.6%

order
Text

Missing 

Distinct404
Distinct (%)< 0.1%
Missing53019
Missing (%)1.2%
Memory size34.5 MiB
2025-01-14T11:45:46.882442image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length31
Mean length9.299688615
Min length6

Characters and Unicode

Total characters41501181
Distinct characters51
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)< 0.1%

Sample

1st rowCorallinales
2nd rowFabales
3rd rowCommelinales
4th rowOxalidales
5th rowPoales
ValueCountFrequency (%)
poales 702157
 
15.7%
asterales 380253
 
8.5%
lamiales 266378
 
6.0%
fabales 254592
 
5.7%
malpighiales 211605
 
4.7%
polypodiales 193095
 
4.3%
gentianales 180579
 
4.0%
myrtales 158308
 
3.5%
caryophyllales 147659
 
3.3%
ericales 129764
 
2.9%
Other values (398) 1839979
41.2%
2025-01-14T11:45:47.127797image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 6796977
16.4%
l 5858220
14.1%
e 5561572
13.4%
s 5364064
12.9%
i 2260328
 
5.4%
o 2043726
 
4.9%
r 1726800
 
4.2%
n 1206408
 
2.9%
t 1060667
 
2.6%
P 1016591
 
2.4%
Other values (41) 8605828
20.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 37031041
89.2%
Uppercase Letter 4462642
 
10.8%
Other Punctuation 5771
 
< 0.1%
Space Separator 1727
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 6796977
18.4%
l 5858220
15.8%
e 5561572
15.0%
s 5364064
14.5%
i 2260328
 
6.1%
o 2043726
 
5.5%
r 1726800
 
4.7%
n 1206408
 
3.3%
t 1060667
 
2.9%
p 1000669
 
2.7%
Other values (15) 4151610
11.2%
Uppercase Letter
ValueCountFrequency (%)
P 1016591
22.8%
A 581960
13.0%
M 481360
10.8%
L 454975
10.2%
C 361177
 
8.1%
F 296457
 
6.6%
S 246396
 
5.5%
G 227690
 
5.1%
R 187767
 
4.2%
E 144300
 
3.2%
Other values (14) 463969
10.4%
Other Punctuation
ValueCountFrequency (%)
. 5771
100.0%
Space Separator
ValueCountFrequency (%)
1727
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 41493683
> 99.9%
Common 7498
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 6796977
16.4%
l 5858220
14.1%
e 5561572
13.4%
s 5364064
12.9%
i 2260328
 
5.4%
o 2043726
 
4.9%
r 1726800
 
4.2%
n 1206408
 
2.9%
t 1060667
 
2.6%
P 1016591
 
2.4%
Other values (39) 8598330
20.7%
Common
ValueCountFrequency (%)
. 5771
77.0%
1727
 
23.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41501181
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 6796977
16.4%
l 5858220
14.1%
e 5561572
13.4%
s 5364064
12.9%
i 2260328
 
5.4%
o 2043726
 
4.9%
r 1726800
 
4.2%
n 1206408
 
2.9%
t 1060667
 
2.6%
P 1016591
 
2.4%
Other values (41) 8605828
20.7%

family
Text

Missing 

Distinct1349
Distinct (%)< 0.1%
Missing49040
Missing (%)1.1%
Memory size34.5 MiB
2025-01-14T11:45:47.301578image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length38
Median length34
Mean length10.77015601
Min length6

Characters and Unicode

Total characters48106205
Distinct characters57
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)< 0.1%

Sample

1st rowLithothamniaceae
2nd rowFabaceae
3rd rowCommelinaceae
4th rowConnaraceae
5th rowPoaceae
ValueCountFrequency (%)
poaceae 502389
 
11.2%
asteraceae 358301
 
8.0%
fabaceae 237916
 
5.3%
cyperaceae 139791
 
3.1%
rubiaceae 119885
 
2.7%
melastomataceae 73747
 
1.6%
parmeliaceae 66931
 
1.5%
rosaceae 65723
 
1.5%
lamiaceae 62361
 
1.4%
euphorbiaceae 59298
 
1.3%
Other values (1336) 2800225
62.4%
2025-01-14T11:45:47.547047image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 10978354
22.8%
e 10624096
22.1%
c 5308142
11.0%
i 2196406
 
4.6%
r 2091808
 
4.3%
o 2020260
 
4.2%
l 1542594
 
3.2%
t 1385215
 
2.9%
n 1300651
 
2.7%
s 1002425
 
2.1%
Other values (47) 9656254
20.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 43607763
90.6%
Uppercase Letter 4466621
 
9.3%
Space Separator 19946
 
< 0.1%
Other Punctuation 11687
 
< 0.1%
Open Punctuation 94
 
< 0.1%
Close Punctuation 94
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 10978354
25.2%
e 10624096
24.4%
c 5308142
12.2%
i 2196406
 
5.0%
r 2091808
 
4.8%
o 2020260
 
4.6%
l 1542594
 
3.5%
t 1385215
 
3.2%
n 1300651
 
3.0%
s 1002425
 
2.3%
Other values (16) 5157812
11.8%
Uppercase Letter
ValueCountFrequency (%)
P 961089
21.5%
A 673867
15.1%
C 509106
11.4%
R 296480
 
6.6%
F 267712
 
6.0%
S 249020
 
5.6%
M 248845
 
5.6%
L 198706
 
4.4%
B 172370
 
3.9%
O 153205
 
3.4%
Other values (16) 736221
16.5%
Other Punctuation
ValueCountFrequency (%)
. 11679
99.9%
? 8
 
0.1%
Space Separator
ValueCountFrequency (%)
19946
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 48074384
99.9%
Common 31821
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 10978354
22.8%
e 10624096
22.1%
c 5308142
11.0%
i 2196406
 
4.6%
r 2091808
 
4.4%
o 2020260
 
4.2%
l 1542594
 
3.2%
t 1385215
 
2.9%
n 1300651
 
2.7%
s 1002425
 
2.1%
Other values (42) 9624433
20.0%
Common
ValueCountFrequency (%)
19946
62.7%
. 11679
36.7%
( 94
 
0.3%
) 94
 
0.3%
? 8
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48106205
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 10978354
22.8%
e 10624096
22.1%
c 5308142
11.0%
i 2196406
 
4.6%
r 2091808
 
4.3%
o 2020260
 
4.2%
l 1542594
 
3.2%
t 1385215
 
2.9%
n 1300651
 
2.7%
s 1002425
 
2.1%
Other values (47) 9656254
20.1%

genus
Text

Distinct19533
Distinct (%)0.4%
Missing13790
Missing (%)0.3%
Memory size34.5 MiB
2025-01-14T11:45:47.760958image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length28
Median length21
Mean length8.779886629
Min length2

Characters and Unicode

Total characters39525917
Distinct characters59
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2723 ?
Unique (%)0.1%

Sample

1st rowLithothamnion
2nd rowAmicia
3rd rowTripogandra
4th rowConnarus
5th rowTrichoneura
ValueCountFrequency (%)
carex 58129
 
1.3%
indet 34179
 
0.8%
poa 30191
 
0.7%
cyperus 27842
 
0.6%
cladonia 26929
 
0.6%
paspalum 26142
 
0.6%
solanum 24852
 
0.6%
miconia 24577
 
0.5%
eragrostis 23701
 
0.5%
asplenium 20032
 
0.4%
Other values (19524) 4220155
93.4%
2025-01-14T11:45:48.033994image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4832994
 
12.2%
i 3638319
 
9.2%
o 2765978
 
7.0%
e 2764006
 
7.0%
r 2582882
 
6.5%
l 2161942
 
5.5%
n 2070715
 
5.2%
s 2058198
 
5.2%
u 1993081
 
5.0%
t 1685888
 
4.3%
Other values (49) 12971914
32.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34974819
88.5%
Uppercase Letter 4501774
 
11.4%
Other Punctuation 34178
 
0.1%
Space Separator 14858
 
< 0.1%
Open Punctuation 97
 
< 0.1%
Close Punctuation 97
 
< 0.1%
Dash Punctuation 94
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4832994
13.8%
i 3638319
10.4%
o 2765978
 
7.9%
e 2764006
 
7.9%
r 2582882
 
7.4%
l 2161942
 
6.2%
n 2070715
 
5.9%
s 2058198
 
5.9%
u 1993081
 
5.7%
t 1685888
 
4.8%
Other values (17) 8420816
24.1%
Uppercase Letter
ValueCountFrequency (%)
C 641047
14.2%
P 589254
13.1%
S 440682
9.8%
A 403961
 
9.0%
M 286195
 
6.4%
E 238456
 
5.3%
L 237999
 
5.3%
D 211365
 
4.7%
B 192319
 
4.3%
H 182246
 
4.0%
Other values (16) 1078250
24.0%
Other Punctuation
ValueCountFrequency (%)
. 34174
> 99.9%
/ 4
 
< 0.1%
Space Separator
ValueCountFrequency (%)
14858
100.0%
Open Punctuation
ValueCountFrequency (%)
( 97
100.0%
Close Punctuation
ValueCountFrequency (%)
) 97
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 39476593
99.9%
Common 49324
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4832994
 
12.2%
i 3638319
 
9.2%
o 2765978
 
7.0%
e 2764006
 
7.0%
r 2582882
 
6.5%
l 2161942
 
5.5%
n 2070715
 
5.2%
s 2058198
 
5.2%
u 1993081
 
5.0%
t 1685888
 
4.3%
Other values (43) 12922590
32.7%
Common
ValueCountFrequency (%)
. 34174
69.3%
14858
30.1%
( 97
 
0.2%
) 97
 
0.2%
- 94
 
0.2%
/ 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39525225
> 99.9%
None 692
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4832994
 
12.2%
i 3638319
 
9.2%
o 2765978
 
7.0%
e 2764006
 
7.0%
r 2582882
 
6.5%
l 2161942
 
5.5%
n 2070715
 
5.2%
s 2058198
 
5.2%
u 1993081
 
5.0%
t 1685888
 
4.3%
Other values (48) 12971222
32.8%
None
ValueCountFrequency (%)
ë 692
100.0%

subgenus
Text

Missing 

Distinct14
Distinct (%)15.7%
Missing4515572
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:48.109114image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length17
Mean length12.14606742
Min length6

Characters and Unicode

Total characters1081
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)5.6%

Sample

1st rowChoanopsis
2nd rowLeptostemonum
3rd rowLeptostemonum
4th rowPseudopoa
5th rowLeptostemonum
ValueCountFrequency (%)
leptostemonum 41
45.6%
meniscium 13
 
14.4%
goniophlebiopteris 10
 
11.1%
pseudopoa 6
 
6.7%
choanopsis 5
 
5.6%
penzigia 3
 
3.3%
arenariae 2
 
2.2%
trichochloa 2
 
2.2%
pseudolysimachium 2
 
2.2%
limnochloa 1
 
1.1%
Other values (5) 5
 
5.6%
2025-01-14T11:45:48.234678image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 147
13.6%
e 131
12.1%
m 100
9.3%
t 93
8.6%
s 84
7.8%
i 82
7.6%
n 78
7.2%
p 74
6.8%
u 66
 
6.1%
L 42
 
3.9%
Other values (22) 184
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 991
91.7%
Uppercase Letter 88
 
8.1%
Other Punctuation 1
 
0.1%
Space Separator 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 147
14.8%
e 131
13.2%
m 100
10.1%
t 93
9.4%
s 84
8.5%
i 82
8.3%
n 78
7.9%
p 74
7.5%
u 66
6.7%
a 28
 
2.8%
Other values (11) 108
10.9%
Uppercase Letter
ValueCountFrequency (%)
L 42
47.7%
M 13
 
14.8%
P 11
 
12.5%
G 10
 
11.4%
C 6
 
6.8%
A 2
 
2.3%
T 2
 
2.3%
D 1
 
1.1%
F 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
§ 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1079
99.8%
Common 2
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 147
13.6%
e 131
12.1%
m 100
9.3%
t 93
8.6%
s 84
7.8%
i 82
7.6%
n 78
7.2%
p 74
6.9%
u 66
 
6.1%
L 42
 
3.9%
Other values (20) 182
16.9%
Common
ValueCountFrequency (%)
§ 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1080
99.9%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 147
13.6%
e 131
12.1%
m 100
9.3%
t 93
8.6%
s 84
7.8%
i 82
7.6%
n 78
7.2%
p 74
6.9%
u 66
 
6.1%
L 42
 
3.9%
Other values (21) 183
16.9%
None
ValueCountFrequency (%)
§ 1
100.0%

specificEpithet
Text

Distinct75699
Distinct (%)1.7%
Missing19440
Missing (%)0.4%
Memory size34.5 MiB
2025-01-14T11:45:48.448301image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length27
Mean length8.783425904
Min length2

Characters and Unicode

Total characters39492224
Distinct characters55
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20935 ?
Unique (%)0.5%

Sample

1st rowcalcareum
2nd rowglandulosa
3rd rowglandulosa
4th rowsteyermarkii
5th rowgrandiglumis
ValueCountFrequency (%)
sp 270345
 
6.0%
canadensis 11707
 
0.3%
guianensis 11466
 
0.3%
americana 11279
 
0.3%
latifolia 11149
 
0.2%
repens 10154
 
0.2%
parviflora 10009
 
0.2%
occidentalis 9667
 
0.2%
gracilis 9142
 
0.2%
indica 9037
 
0.2%
Other values (75609) 4133864
91.9%
2025-01-14T11:45:48.746312image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5237374
13.3%
i 4468913
11.3%
s 3076318
 
7.8%
e 2756650
 
7.0%
r 2532177
 
6.4%
l 2515617
 
6.4%
n 2415168
 
6.1%
u 2268906
 
5.7%
o 2256284
 
5.7%
t 2041234
 
5.2%
Other values (45) 9923583
25.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39191766
99.2%
Other Punctuation 278333
 
0.7%
Dash Punctuation 20172
 
0.1%
Space Separator 1598
 
< 0.1%
Decimal Number 288
 
< 0.1%
Open Punctuation 30
 
< 0.1%
Close Punctuation 30
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 5237374
13.4%
i 4468913
11.4%
s 3076318
 
7.8%
e 2756650
 
7.0%
r 2532177
 
6.5%
l 2515617
 
6.4%
n 2415168
 
6.2%
u 2268906
 
5.8%
o 2256284
 
5.8%
t 2041234
 
5.2%
Other values (19) 9623125
24.6%
Decimal Number
ValueCountFrequency (%)
1 93
32.3%
2 48
16.7%
0 41
14.2%
8 39
13.5%
6 25
 
8.7%
3 18
 
6.2%
5 9
 
3.1%
4 9
 
3.1%
7 5
 
1.7%
9 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 278069
99.9%
" 114
 
< 0.1%
' 90
 
< 0.1%
/ 33
 
< 0.1%
? 14
 
< 0.1%
# 11
 
< 0.1%
, 1
 
< 0.1%
* 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 28
93.3%
[ 2
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 28
93.3%
] 2
 
6.7%
Math Symbol
ValueCountFrequency (%)
× 4
57.1%
~ 3
42.9%
Dash Punctuation
ValueCountFrequency (%)
- 20172
100.0%
Space Separator
ValueCountFrequency (%)
1598
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 39191766
99.2%
Common 300458
 
0.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 5237374
13.4%
i 4468913
11.4%
s 3076318
 
7.8%
e 2756650
 
7.0%
r 2532177
 
6.5%
l 2515617
 
6.4%
n 2415168
 
6.2%
u 2268906
 
5.8%
o 2256284
 
5.8%
t 2041234
 
5.2%
Other values (19) 9623125
24.6%
Common
ValueCountFrequency (%)
. 278069
92.5%
- 20172
 
6.7%
1598
 
0.5%
" 114
 
< 0.1%
1 93
 
< 0.1%
' 90
 
< 0.1%
2 48
 
< 0.1%
0 41
 
< 0.1%
8 39
 
< 0.1%
/ 33
 
< 0.1%
Other values (16) 161
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39492142
> 99.9%
None 82
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 5237374
13.3%
i 4468913
11.3%
s 3076318
 
7.8%
e 2756650
 
7.0%
r 2532177
 
6.4%
l 2515617
 
6.4%
n 2415168
 
6.1%
u 2268906
 
5.7%
o 2256284
 
5.7%
t 2041234
 
5.2%
Other values (41) 9923501
25.1%
None
ValueCountFrequency (%)
ë 68
82.9%
ü 9
 
11.0%
× 4
 
4.9%
ñ 1
 
1.2%

infraspecificEpithet
Text

Missing 

Distinct13508
Distinct (%)4.2%
Missing4196068
Missing (%)92.9%
Memory size34.5 MiB
2025-01-14T11:45:48.959658image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length33
Median length29
Mean length9.193180076
Min length1

Characters and Unicode

Total characters2938076
Distinct characters48
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4773 ?
Unique (%)1.5%

Sample

1st rowoxyphylla
2nd rowsubalpinum
3rd rowpurpurescens
4th rowpubescens
5th rowhirsuta
ValueCountFrequency (%)
acuminatum 4368
 
1.4%
pubescens 1879
 
0.6%
secunda 1646
 
0.5%
dichotomum 1521
 
0.5%
americana 1487
 
0.5%
gracilis 1466
 
0.5%
angustifolia 1339
 
0.4%
typica 1218
 
0.4%
occidentalis 1214
 
0.4%
glauca 1198
 
0.4%
Other values (13459) 302708
94.6%
2025-01-14T11:45:49.251139image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 401235
13.7%
i 336149
11.4%
s 216184
 
7.4%
e 204762
 
7.0%
l 195545
 
6.7%
n 184185
 
6.3%
r 181755
 
6.2%
u 176685
 
6.0%
o 167405
 
5.7%
t 150042
 
5.1%
Other values (38) 724129
24.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2936297
99.9%
Dash Punctuation 833
 
< 0.1%
Space Separator 451
 
< 0.1%
Other Punctuation 290
 
< 0.1%
Uppercase Letter 90
 
< 0.1%
Open Punctuation 55
 
< 0.1%
Close Punctuation 55
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 401235
13.7%
i 336149
11.4%
s 216184
 
7.4%
e 204762
 
7.0%
l 195545
 
6.7%
n 184185
 
6.3%
r 181755
 
6.2%
u 176685
 
6.0%
o 167405
 
5.7%
t 150042
 
5.1%
Other values (18) 722350
24.6%
Uppercase Letter
ValueCountFrequency (%)
I 23
25.6%
F 22
24.4%
C 14
15.6%
A 11
12.2%
B 7
 
7.8%
O 4
 
4.4%
H 4
 
4.4%
M 2
 
2.2%
D 1
 
1.1%
V 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 234
80.7%
' 25
 
8.6%
? 19
 
6.6%
" 12
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 833
100.0%
Space Separator
ValueCountFrequency (%)
451
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Math Symbol
ValueCountFrequency (%)
× 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2936387
99.9%
Common 1689
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 401235
13.7%
i 336149
11.4%
s 216184
 
7.4%
e 204762
 
7.0%
l 195545
 
6.7%
n 184185
 
6.3%
r 181755
 
6.2%
u 176685
 
6.0%
o 167405
 
5.7%
t 150042
 
5.1%
Other values (29) 722440
24.6%
Common
ValueCountFrequency (%)
- 833
49.3%
451
26.7%
. 234
 
13.9%
( 55
 
3.3%
) 55
 
3.3%
' 25
 
1.5%
? 19
 
1.1%
" 12
 
0.7%
× 5
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2938068
> 99.9%
None 8
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 401235
13.7%
i 336149
11.4%
s 216184
 
7.4%
e 204762
 
7.0%
l 195545
 
6.7%
n 184185
 
6.3%
r 181755
 
6.2%
u 176685
 
6.0%
o 167405
 
5.7%
t 150042
 
5.1%
Other values (35) 724121
24.6%
None
ValueCountFrequency (%)
× 5
62.5%
ë 2
 
25.0%
ß 1
 
12.5%

cultivarEpithet
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing4515659
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:49.314849image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length14.5
Mean length14.5
Min length13

Characters and Unicode

Total characters29
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowMelica torreyana
2nd rowDiplazium sp.
ValueCountFrequency (%)
melica 1
25.0%
torreyana 1
25.0%
diplazium 1
25.0%
sp 1
25.0%
2025-01-14T11:45:49.428701image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
13.8%
i 3
 
10.3%
r 2
 
6.9%
l 2
 
6.9%
2
 
6.9%
e 2
 
6.9%
p 2
 
6.9%
D 1
 
3.4%
s 1
 
3.4%
m 1
 
3.4%
Other values (9) 9
31.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
82.8%
Space Separator 2
 
6.9%
Uppercase Letter 2
 
6.9%
Other Punctuation 1
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4
16.7%
i 3
12.5%
r 2
 
8.3%
l 2
 
8.3%
e 2
 
8.3%
p 2
 
8.3%
s 1
 
4.2%
m 1
 
4.2%
u 1
 
4.2%
z 1
 
4.2%
Other values (5) 5
20.8%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
M 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 26
89.7%
Common 3
 
10.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4
15.4%
i 3
11.5%
r 2
 
7.7%
l 2
 
7.7%
e 2
 
7.7%
p 2
 
7.7%
D 1
 
3.8%
s 1
 
3.8%
m 1
 
3.8%
u 1
 
3.8%
Other values (7) 7
26.9%
Common
ValueCountFrequency (%)
2
66.7%
. 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4
13.8%
i 3
 
10.3%
r 2
 
6.9%
l 2
 
6.9%
2
 
6.9%
e 2
 
6.9%
p 2
 
6.9%
D 1
 
3.4%
s 1
 
3.4%
m 1
 
3.4%
Other values (9) 9
31.0%

taxonRank
Text

Missing 

Distinct28
Distinct (%)< 0.1%
Missing4196350
Missing (%)92.9%
Memory size34.5 MiB
2025-01-14T11:45:49.485632image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length7
Mean length7.875528873
Min length2

Characters and Unicode

Total characters2514743
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowvariety
2nd rowVariety
3rd rowvariety
4th rowsubspecies
5th rowVariety
ValueCountFrequency (%)
variety 207363
64.9%
subspecies 101047
31.6%
forma 8236
 
2.6%
var 2270
 
0.7%
form 85
 
< 0.1%
subvariety 81
 
< 0.1%
aff 73
 
< 0.1%
nothosubsp 57
 
< 0.1%
agg 18
 
< 0.1%
fo 18
 
< 0.1%
Other values (15) 63
 
< 0.1%
2025-01-14T11:45:49.597464image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 409561
16.3%
i 308499
12.3%
s 303355
12.1%
a 218079
8.7%
r 218075
8.7%
t 207516
8.3%
y 207450
8.2%
v 181926
7.2%
u 101201
 
4.0%
b 101194
 
4.0%
Other values (16) 257887
10.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2484340
98.8%
Uppercase Letter 28022
 
1.1%
Other Punctuation 2367
 
0.1%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 409561
16.5%
i 308499
12.4%
s 303355
12.2%
a 218079
8.8%
r 218075
8.8%
t 207516
8.4%
y 207450
8.4%
v 181926
7.3%
u 101201
 
4.1%
b 101194
 
4.1%
Other values (11) 227484
9.2%
Uppercase Letter
ValueCountFrequency (%)
V 27814
99.3%
F 208
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 2367
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 7
100.0%
Close Punctuation
ValueCountFrequency (%)
] 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2512362
99.9%
Common 2381
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 409561
16.3%
i 308499
12.3%
s 303355
12.1%
a 218079
8.7%
r 218075
8.7%
t 207516
8.3%
y 207450
8.3%
v 181926
7.2%
u 101201
 
4.0%
b 101194
 
4.0%
Other values (13) 255506
10.2%
Common
ValueCountFrequency (%)
. 2367
99.4%
[ 7
 
0.3%
] 7
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2514743
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 409561
16.3%
i 308499
12.3%
s 303355
12.1%
a 218079
8.7%
r 218075
8.7%
t 207516
8.3%
y 207450
8.2%
v 181926
7.2%
u 101201
 
4.0%
b 101194
 
4.0%
Other values (16) 257887
10.3%

scientificNameAuthorship
Text

Missing 

Distinct61211
Distinct (%)1.5%
Missing491289
Missing (%)10.9%
Memory size34.5 MiB
2025-01-14T11:45:49.789752image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length255
Median length63
Mean length11.67467396
Min length2

Characters and Unicode

Total characters46983231
Distinct characters115
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12830 ?
Unique (%)0.3%

Sample

1st rowKunth
2nd row(Seub.) Rohweder
3rd rowPrance
4th row(Nees) Ekman
5th row(Britton ex Rusby) Wiehler
ValueCountFrequency (%)
l 655549
 
7.4%
528030
 
6.0%
ex 293982
 
3.3%
a 184606
 
2.1%
dc 137922
 
1.6%
kunth 108763
 
1.2%
gray 104768
 
1.2%
benth 100384
 
1.1%
sw 88430
 
1.0%
hook 85187
 
1.0%
Other values (10671) 6515117
74.0%
2025-01-14T11:45:50.061883image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 5755821
 
12.3%
4778366
 
10.2%
e 2841039
 
6.0%
r 2154959
 
4.6%
a 1898912
 
4.0%
l 1877752
 
4.0%
n 1788431
 
3.8%
( 1676769
 
3.6%
) 1676769
 
3.6%
o 1598443
 
3.4%
Other values (105) 20935970
44.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23970208
51.0%
Uppercase Letter 8556492
 
18.2%
Other Punctuation 6296715
 
13.4%
Space Separator 4778366
 
10.2%
Open Punctuation 1676769
 
3.6%
Close Punctuation 1676769
 
3.6%
Dash Punctuation 27912
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2841039
11.9%
r 2154959
 
9.0%
a 1898912
 
7.9%
l 1877752
 
7.8%
n 1788431
 
7.5%
o 1598443
 
6.7%
t 1484295
 
6.2%
i 1367987
 
5.7%
h 1198850
 
5.0%
u 1056566
 
4.4%
Other values (54) 6702974
28.0%
Uppercase Letter
ValueCountFrequency (%)
L 1021813
11.9%
S 792307
 
9.3%
B 645199
 
7.5%
H 609960
 
7.1%
M 590105
 
6.9%
C 571360
 
6.7%
A 491164
 
5.7%
R 469346
 
5.5%
G 421747
 
4.9%
D 402530
 
4.7%
Other values (29) 2540961
29.7%
Other Punctuation
ValueCountFrequency (%)
. 5755821
91.4%
& 528658
 
8.4%
' 6283
 
0.1%
, 4298
 
0.1%
\ 1631
 
< 0.1%
? 19
 
< 0.1%
; 4
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
4778366
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1676769
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1676769
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27912
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 32526700
69.2%
Common 14456531
30.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2841039
 
8.7%
r 2154959
 
6.6%
a 1898912
 
5.8%
l 1877752
 
5.8%
n 1788431
 
5.5%
o 1598443
 
4.9%
t 1484295
 
4.6%
i 1367987
 
4.2%
h 1198850
 
3.7%
u 1056566
 
3.2%
Other values (93) 15259466
46.9%
Common
ValueCountFrequency (%)
. 5755821
39.8%
4778366
33.1%
( 1676769
 
11.6%
) 1676769
 
11.6%
& 528658
 
3.7%
- 27912
 
0.2%
' 6283
 
< 0.1%
, 4298
 
< 0.1%
\ 1631
 
< 0.1%
? 19
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46805325
99.6%
None 177906
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 5755821
 
12.3%
4778366
 
10.2%
e 2841039
 
6.1%
r 2154959
 
4.6%
a 1898912
 
4.1%
l 1877752
 
4.0%
n 1788431
 
3.8%
( 1676769
 
3.6%
) 1676769
 
3.6%
o 1598443
 
3.4%
Other values (54) 20758064
44.3%
None
ValueCountFrequency (%)
ü 62724
35.3%
é 39116
22.0%
ö 26088
14.7%
ä 7921
 
4.5%
á 7902
 
4.4%
Á 7616
 
4.3%
ø 4718
 
2.7%
ó 3620
 
2.0%
Ø 2882
 
1.6%
è 2708
 
1.5%
Other values (41) 12611
 
7.1%

vernacularName
Text

Missing 

Distinct2
Distinct (%)66.7%
Missing4515658
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:50.118034image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.666666667
Min length7

Characters and Unicode

Total characters23
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowHolotype
2nd rowIsotype
3rd rowHolotype
ValueCountFrequency (%)
holotype 2
66.7%
isotype 1
33.3%
2025-01-14T11:45:50.216997image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 5
21.7%
t 3
13.0%
y 3
13.0%
p 3
13.0%
e 3
13.0%
H 2
 
8.7%
l 2
 
8.7%
I 1
 
4.3%
s 1
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20
87.0%
Uppercase Letter 3
 
13.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 5
25.0%
t 3
15.0%
y 3
15.0%
p 3
15.0%
e 3
15.0%
l 2
 
10.0%
s 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
H 2
66.7%
I 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 23
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 5
21.7%
t 3
13.0%
y 3
13.0%
p 3
13.0%
e 3
13.0%
H 2
 
8.7%
l 2
 
8.7%
I 1
 
4.3%
s 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 5
21.7%
t 3
13.0%
y 3
13.0%
p 3
13.0%
e 3
13.0%
H 2
 
8.7%
l 2
 
8.7%
I 1
 
4.3%
s 1
 
4.3%

nomenclaturalCode
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing4515660
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:50.266576image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters17
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowSkog, Laurence E.
ValueCountFrequency (%)
skog 1
33.3%
laurence 1
33.3%
e 1
33.3%
2025-01-14T11:45:50.366896image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
 
11.8%
e 2
 
11.8%
S 1
 
5.9%
k 1
 
5.9%
o 1
 
5.9%
g 1
 
5.9%
, 1
 
5.9%
L 1
 
5.9%
a 1
 
5.9%
u 1
 
5.9%
Other values (5) 5
29.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10
58.8%
Uppercase Letter 3
 
17.6%
Space Separator 2
 
11.8%
Other Punctuation 2
 
11.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2
20.0%
k 1
10.0%
o 1
10.0%
g 1
10.0%
a 1
10.0%
u 1
10.0%
r 1
10.0%
n 1
10.0%
c 1
10.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
L 1
33.3%
E 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13
76.5%
Common 4
 
23.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2
15.4%
S 1
7.7%
k 1
7.7%
o 1
7.7%
g 1
7.7%
L 1
7.7%
a 1
7.7%
u 1
7.7%
r 1
7.7%
n 1
7.7%
Other values (2) 2
15.4%
Common
ValueCountFrequency (%)
2
50.0%
, 1
25.0%
. 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
 
11.8%
e 2
 
11.8%
S 1
 
5.9%
k 1
 
5.9%
o 1
 
5.9%
g 1
 
5.9%
, 1
 
5.9%
L 1
 
5.9%
a 1
 
5.9%
u 1
 
5.9%
Other values (5) 5
29.4%

nomenclaturalStatus
Text

Missing 

Distinct2
Distinct (%)100.0%
Missing4515659
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:50.426378image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length51
Median length49.5
Mean length49.5
Min length48

Characters and Unicode

Total characters99
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowPlantae, Monocotyledonae, Poales, Poaceae, Pooideae
2nd rowPlantae, Pteridophyte, Polypodiales, Athyriaceae
ValueCountFrequency (%)
plantae 2
22.2%
monocotyledonae 1
11.1%
poales 1
11.1%
poaceae 1
11.1%
pooideae 1
11.1%
pteridophyte 1
11.1%
polypodiales 1
11.1%
athyriaceae 1
11.1%
2025-01-14T11:45:50.549608image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 14
14.1%
a 12
12.1%
o 11
11.1%
7
 
7.1%
, 7
 
7.1%
P 7
 
7.1%
t 6
 
6.1%
l 6
 
6.1%
n 4
 
4.0%
y 4
 
4.0%
Other values (9) 21
21.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 76
76.8%
Uppercase Letter 9
 
9.1%
Space Separator 7
 
7.1%
Other Punctuation 7
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 14
18.4%
a 12
15.8%
o 11
14.5%
t 6
7.9%
l 6
7.9%
n 4
 
5.3%
y 4
 
5.3%
d 4
 
5.3%
i 4
 
5.3%
c 3
 
3.9%
Other values (4) 8
10.5%
Uppercase Letter
ValueCountFrequency (%)
P 7
77.8%
M 1
 
11.1%
A 1
 
11.1%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 85
85.9%
Common 14
 
14.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 14
16.5%
a 12
14.1%
o 11
12.9%
P 7
8.2%
t 6
7.1%
l 6
7.1%
n 4
 
4.7%
y 4
 
4.7%
d 4
 
4.7%
i 4
 
4.7%
Other values (7) 13
15.3%
Common
ValueCountFrequency (%)
7
50.0%
, 7
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 14
14.1%
a 12
12.1%
o 11
11.1%
7
 
7.1%
, 7
 
7.1%
P 7
 
7.1%
t 6
 
6.1%
l 6
 
6.1%
n 4
 
4.0%
y 4
 
4.0%
Other values (9) 21
21.2%

taxonRemarks
Text

Constant  Missing 

Distinct1
Distinct (%)50.0%
Missing4515659
Missing (%)> 99.9%
Memory size34.5 MiB
2025-01-14T11:45:50.594291image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters14
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPlantae
2nd rowPlantae
ValueCountFrequency (%)
plantae 2
100.0%
2025-01-14T11:45:50.689476image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
28.6%
P 2
14.3%
l 2
14.3%
n 2
14.3%
t 2
14.3%
e 2
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12
85.7%
Uppercase Letter 2
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4
33.3%
l 2
16.7%
n 2
16.7%
t 2
16.7%
e 2
16.7%
Uppercase Letter
ValueCountFrequency (%)
P 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4
28.6%
P 2
14.3%
l 2
14.3%
n 2
14.3%
t 2
14.3%
e 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4
28.6%
P 2
14.3%
l 2
14.3%
n 2
14.3%
t 2
14.3%
e 2
14.3%